Overview

Dataset statistics

Number of variables62
Number of observations113
Missing cells2742
Missing cells (%)39.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory54.9 KiB
Average record size in memory497.1 B

Variable types

Numeric14
Categorical39
Unsupported9

Alerts

airdate has constant value "2020-12-30" Constant
url has a high cardinality: 113 distinct values High cardinality
name has a high cardinality: 88 distinct values High cardinality
_links.self.href has a high cardinality: 113 distinct values High cardinality
_embedded.show.url has a high cardinality: 72 distinct values High cardinality
_embedded.show.name has a high cardinality: 72 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 53 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 64 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 68 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 68 distinct values High cardinality
_embedded.show.summary has a high cardinality: 63 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 72 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 72 distinct values High cardinality
id is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
season is highly correlated with _embedded.show.id and 3 other fieldsHigh correlation
number is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.weight and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 6 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 12 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 3 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 7 other fieldsHigh correlation
id is highly correlated with _embedded.show.externals.tvrageHigh correlation
season is highly correlated with number and 2 other fieldsHigh correlation
number is highly correlated with season and 2 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 4 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.id and 5 other fieldsHigh correlation
id is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
season is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
number is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 4 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.externals.tvrage and 1 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 5 other fieldsHigh correlation
id is highly correlated with name and 39 other fieldsHigh correlation
name is highly correlated with id and 40 other fieldsHigh correlation
season is highly correlated with name and 18 other fieldsHigh correlation
number is highly correlated with name and 21 other fieldsHigh correlation
type is highly correlated with id and 24 other fieldsHigh correlation
airtime is highly correlated with id and 35 other fieldsHigh correlation
airstamp is highly correlated with id and 41 other fieldsHigh correlation
runtime is highly correlated with name and 31 other fieldsHigh correlation
summary is highly correlated with id and 36 other fieldsHigh correlation
rating.average is highly correlated with id and 32 other fieldsHigh correlation
image.medium is highly correlated with id and 37 other fieldsHigh correlation
image.original is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.language is highly correlated with name and 37 other fieldsHigh correlation
_embedded.show.status is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 42 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.externals.tvrage is highly correlated with name and 20 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with name and 32 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 36 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 28 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 28 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 32 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 30 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 30 other fieldsHigh correlation
number has 2 (1.8%) missing values Missing
runtime has 8 (7.1%) missing values Missing
summary has 72 (63.7%) missing values Missing
rating.average has 96 (85.0%) missing values Missing
image.medium has 70 (61.9%) missing values Missing
image.original has 70 (61.9%) missing values Missing
_embedded.show.runtime has 50 (44.2%) missing values Missing
_embedded.show.averageRuntime has 5 (4.4%) missing values Missing
_embedded.show.ended has 56 (49.6%) missing values Missing
_embedded.show.officialSite has 12 (10.6%) missing values Missing
_embedded.show.rating.average has 96 (85.0%) missing values Missing
_embedded.show.network has 113 (100.0%) missing values Missing
_embedded.show.webChannel.country has 113 (100.0%) missing values Missing
_embedded.show.webChannel.officialSite has 24 (21.2%) missing values Missing
_embedded.show.dvdCountry has 113 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 110 (97.3%) missing values Missing
_embedded.show.externals.thetvdb has 31 (27.4%) missing values Missing
_embedded.show.externals.imdb has 52 (46.0%) missing values Missing
_embedded.show.image.medium has 4 (3.5%) missing values Missing
_embedded.show.image.original has 4 (3.5%) missing values Missing
_embedded.show.summary has 9 (8.0%) missing values Missing
_embedded.show.webChannel.country.name has 67 (59.3%) missing values Missing
_embedded.show.webChannel.country.code has 67 (59.3%) missing values Missing
_embedded.show.webChannel.country.timezone has 67 (59.3%) missing values Missing
image has 113 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 108 (95.6%) missing values Missing
_embedded.show.dvdCountry.name has 111 (98.2%) missing values Missing
_embedded.show.dvdCountry.code has 111 (98.2%) missing values Missing
_embedded.show.dvdCountry.timezone has 111 (98.2%) missing values Missing
_embedded.show.network.id has 107 (94.7%) missing values Missing
_embedded.show.network.name has 107 (94.7%) missing values Missing
_embedded.show.network.country.name has 107 (94.7%) missing values Missing
_embedded.show.network.country.code has 107 (94.7%) missing values Missing
_embedded.show.network.country.timezone has 107 (94.7%) missing values Missing
_embedded.show.network.officialSite has 113 (100.0%) missing values Missing
_embedded.show.image has 113 (100.0%) missing values Missing
_embedded.show.webChannel has 113 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.externals.tvrage is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.dvdCountry.name is uniformly distributed Uniform
_embedded.show.dvdCountry.code is uniformly distributed Uniform
_embedded.show.dvdCountry.timezone is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:50:56.832623
Analysis finished2022-09-06 02:51:17.459816
Duration20.63 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2056845
Minimum1945903
Maximum2386111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:17.530781image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1945903
5-th percentile1972779.8
Q11985599
median1996691
Q32095630
95-th percentile2312221.4
Maximum2386111
Range440208
Interquartile range (IQR)110031

Descriptive statistics

Standard deviation117186.053
Coefficient of variation (CV)0.05697369174
Kurtosis0.6396696583
Mean2056845
Median Absolute Deviation (MAD)16283
Skewness1.456258065
Sum232423485
Variance1.373257102 × 1010
MonotonicityNot monotonic
2022-09-05T21:51:17.650693image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21796151
 
0.9%
19585761
 
0.9%
19957531
 
0.9%
19957521
 
0.9%
19953861
 
0.9%
19957471
 
0.9%
19957461
 
0.9%
19957451
 
0.9%
19957441
 
0.9%
19957431
 
0.9%
Other values (103)103
91.2%
ValueCountFrequency (%)
19459031
0.9%
19585761
0.9%
19588691
0.9%
19644971
0.9%
19644981
0.9%
19702551
0.9%
19744631
0.9%
19753721
0.9%
19760521
0.9%
19760531
0.9%
ValueCountFrequency (%)
23861111
0.9%
23300091
0.9%
23244261
0.9%
23244251
0.9%
23181161
0.9%
23122221
0.9%
23122211
0.9%
23122201
0.9%
23122191
0.9%
23122181
0.9%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/episodes/2179615/kontakty-1x32-kontakty-v-telefone-arsenia-popova-pavel-vola-ekaterina-varnava-ila-sobolev-edgard-zapasnyj
 
1
https://www.tvmaze.com/episodes/1958576/my-bromance-2-5-years-later-1x04-episode-4
 
1
https://www.tvmaze.com/episodes/1995753/sanpa-luci-e-tenebre-di-san-patrignano-1x03-fama
 
1
https://www.tvmaze.com/episodes/1995752/sanpa-luci-e-tenebre-di-san-patrignano-1x02-crescita
 
1
https://www.tvmaze.com/episodes/1995386/sanpa-luci-e-tenebre-di-san-patrignano-1x01-nascita
 
1
Other values (108)
108 

Length

Max length145
Median length107
Mean length83.18584071
Min length58

Characters and Unicode

Total characters9400
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2179615/kontakty-1x32-kontakty-v-telefone-arsenia-popova-pavel-vola-ekaterina-varnava-ila-sobolev-edgard-zapasnyj
2nd rowhttps://www.tvmaze.com/episodes/2001718/zona-komforta-s01-special-zona-komforta-osuitelno-specialnyj-vypusk
3rd rowhttps://www.tvmaze.com/episodes/1987721/passaziry-1x03-kirill
4th rowhttps://www.tvmaze.com/episodes/2386111/xian-feng-jian-yu-lu-1x52-episode-52
5th rowhttps://www.tvmaze.com/episodes/2095630/yi-nian-yong-heng-1x23-episode-23

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179615/kontakty-1x32-kontakty-v-telefone-arsenia-popova-pavel-vola-ekaterina-varnava-ila-sobolev-edgard-zapasnyj1
 
0.9%
https://www.tvmaze.com/episodes/1958576/my-bromance-2-5-years-later-1x04-episode-41
 
0.9%
https://www.tvmaze.com/episodes/1995753/sanpa-luci-e-tenebre-di-san-patrignano-1x03-fama1
 
0.9%
https://www.tvmaze.com/episodes/1995752/sanpa-luci-e-tenebre-di-san-patrignano-1x02-crescita1
 
0.9%
https://www.tvmaze.com/episodes/1995386/sanpa-luci-e-tenebre-di-san-patrignano-1x01-nascita1
 
0.9%
https://www.tvmaze.com/episodes/1995747/best-leftovers-ever-1x08-bland-to-flavor-bomb1
 
0.9%
https://www.tvmaze.com/episodes/1995746/best-leftovers-ever-1x07-fiesta-feast1
 
0.9%
https://www.tvmaze.com/episodes/1995745/best-leftovers-ever-1x06-welcome-to-the-neighborhood1
 
0.9%
https://www.tvmaze.com/episodes/1995744/best-leftovers-ever-1x05-down-home-to-uptown1
 
0.9%
https://www.tvmaze.com/episodes/1995743/best-leftovers-ever-1x04-pot-roast-to-french-toast1
 
0.9%
Other values (103)103
91.2%

Length

2022-09-05T21:51:17.771428image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2179615/kontakty-1x32-kontakty-v-telefone-arsenia-popova-pavel-vola-ekaterina-varnava-ila-sobolev-edgard-zapasnyj1
 
0.9%
https://www.tvmaze.com/episodes/2001718/zona-komforta-s01-special-zona-komforta-osuitelno-specialnyj-vypusk1
 
0.9%
https://www.tvmaze.com/episodes/1987721/passaziry-1x03-kirill1
 
0.9%
https://www.tvmaze.com/episodes/2386111/xian-feng-jian-yu-lu-1x52-episode-521
 
0.9%
https://www.tvmaze.com/episodes/2095630/yi-nian-yong-heng-1x23-episode-231
 
0.9%
https://www.tvmaze.com/episodes/1993659/7-days-of-romance-2x04-episode-41
 
0.9%
https://www.tvmaze.com/episodes/2096304/no-turning-back-romance-1x08-81
 
0.9%
https://www.tvmaze.com/episodes/2324425/unique-lady-2x13-episode-131
 
0.9%
https://www.tvmaze.com/episodes/2324426/unique-lady-2x14-episode-141
 
0.9%
https://www.tvmaze.com/episodes/1998603/unique-lady-2-1x13-episode-131
 
0.9%
Other values (103)103
91.2%

Most occurring characters

ValueCountFrequency (%)
e808
 
8.6%
-762
 
8.1%
s588
 
6.3%
/565
 
6.0%
t562
 
6.0%
o527
 
5.6%
a391
 
4.2%
w372
 
4.0%
i369
 
3.9%
p347
 
3.7%
Other values (30)4109
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6429
68.4%
Decimal Number1305
 
13.9%
Other Punctuation904
 
9.6%
Dash Punctuation762
 
8.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e808
12.6%
s588
 
9.1%
t562
 
8.7%
o527
 
8.2%
a391
 
6.1%
w372
 
5.8%
i369
 
5.7%
p347
 
5.4%
m311
 
4.8%
d268
 
4.2%
Other values (16)1886
29.3%
Decimal Number
ValueCountFrequency (%)
1273
20.9%
2199
15.2%
0169
13.0%
9148
11.3%
5104
 
8.0%
496
 
7.4%
388
 
6.7%
782
 
6.3%
678
 
6.0%
868
 
5.2%
Other Punctuation
ValueCountFrequency (%)
/565
62.5%
.226
 
25.0%
:113
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-762
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6429
68.4%
Common2971
31.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e808
12.6%
s588
 
9.1%
t562
 
8.7%
o527
 
8.2%
a391
 
6.1%
w372
 
5.8%
i369
 
5.7%
p347
 
5.4%
m311
 
4.8%
d268
 
4.2%
Other values (16)1886
29.3%
Common
ValueCountFrequency (%)
-762
25.6%
/565
19.0%
1273
 
9.2%
.226
 
7.6%
2199
 
6.7%
0169
 
5.7%
9148
 
5.0%
:113
 
3.8%
5104
 
3.5%
496
 
3.2%
Other values (4)316
10.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII9400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e808
 
8.6%
-762
 
8.1%
s588
 
6.3%
/565
 
6.0%
t562
 
6.0%
o527
 
5.6%
a391
 
4.2%
w372
 
4.0%
i369
 
3.9%
p347
 
3.7%
Other values (30)4109
43.7%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct88
Distinct (%)77.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Episode 4
 
6
Episode 1
 
5
Episode 6
 
4
Episode 2
 
4
Episode 5
 
3
Other values (83)
91 

Length

Max length96
Median length79
Mean length17.73451327
Min length1

Characters and Unicode

Total characters2004
Distinct characters126
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)67.3%

Sample

1st rowКОНТАКТЫ в телефоне Арсения Попова: Павел Воля, Екатерина Варнава, Илья Соболев, Эдгард Запашный
2nd rowЗона Комфорта. Ошуительно Специальный Выпуск
3rd rowКирилл
4th rowEpisode 52
5th rowEpisode 23

Common Values

ValueCountFrequency (%)
Episode 46
 
5.3%
Episode 15
 
4.4%
Episode 64
 
3.5%
Episode 24
 
3.5%
Episode 53
 
2.7%
Episode 133
 
2.7%
Episode 32
 
1.8%
Episode 252
 
1.8%
Episode 262
 
1.8%
Episode 112
 
1.8%
Other values (78)80
70.8%

Length

2022-09-05T21:51:17.889243image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode52
 
14.4%
the9
 
2.5%
to8
 
2.2%
18
 
2.2%
6
 
1.7%
46
 
1.7%
26
 
1.7%
and4
 
1.1%
20204
 
1.1%
december4
 
1.1%
Other values (222)255
70.4%

Most occurring characters

ValueCountFrequency (%)
249
 
12.4%
e152
 
7.6%
o119
 
5.9%
i99
 
4.9%
s96
 
4.8%
d82
 
4.1%
a73
 
3.6%
p66
 
3.3%
t57
 
2.8%
E55
 
2.7%
Other values (116)956
47.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1314
65.6%
Uppercase Letter262
 
13.1%
Space Separator249
 
12.4%
Decimal Number133
 
6.6%
Other Punctuation32
 
1.6%
Dash Punctuation6
 
0.3%
Close Punctuation3
 
0.1%
Open Punctuation3
 
0.1%
Math Symbol2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e152
 
11.6%
o119
 
9.1%
i99
 
7.5%
s96
 
7.3%
d82
 
6.2%
a73
 
5.6%
p66
 
5.0%
t57
 
4.3%
n51
 
3.9%
r50
 
3.8%
Other values (51)469
35.7%
Uppercase Letter
ValueCountFrequency (%)
E55
21.0%
F12
 
4.6%
D11
 
4.2%
B9
 
3.4%
H9
 
3.4%
T9
 
3.4%
О9
 
3.4%
A9
 
3.4%
G8
 
3.1%
В8
 
3.1%
Other values (33)123
46.9%
Decimal Number
ValueCountFrequency (%)
236
27.1%
126
19.5%
017
12.8%
414
 
10.5%
314
 
10.5%
510
 
7.5%
69
 
6.8%
84
 
3.0%
92
 
1.5%
71
 
0.8%
Other Punctuation
ValueCountFrequency (%)
,15
46.9%
:6
 
18.8%
.5
 
15.6%
?2
 
6.2%
!2
 
6.2%
&1
 
3.1%
/1
 
3.1%
Space Separator
ValueCountFrequency (%)
249
100.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Math Symbol
ValueCountFrequency (%)
|2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1239
61.8%
Common428
 
21.4%
Cyrillic337
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e152
 
12.3%
o119
 
9.6%
i99
 
8.0%
s96
 
7.7%
d82
 
6.6%
a73
 
5.9%
p66
 
5.3%
t57
 
4.6%
E55
 
4.4%
n51
 
4.1%
Other values (43)389
31.4%
Cyrillic
ValueCountFrequency (%)
а30
 
8.9%
и25
 
7.4%
е20
 
5.9%
л19
 
5.6%
о19
 
5.6%
н18
 
5.3%
р15
 
4.5%
т14
 
4.2%
в12
 
3.6%
с10
 
3.0%
Other values (41)155
46.0%
Common
ValueCountFrequency (%)
249
58.2%
236
 
8.4%
126
 
6.1%
017
 
4.0%
,15
 
3.5%
414
 
3.3%
314
 
3.3%
510
 
2.3%
69
 
2.1%
:6
 
1.4%
Other values (12)32
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1656
82.6%
Cyrillic337
 
16.8%
None11
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
15.0%
e152
 
9.2%
o119
 
7.2%
i99
 
6.0%
s96
 
5.8%
d82
 
5.0%
a73
 
4.4%
p66
 
4.0%
t57
 
3.4%
E55
 
3.3%
Other values (58)608
36.7%
Cyrillic
ValueCountFrequency (%)
а30
 
8.9%
и25
 
7.4%
е20
 
5.9%
л19
 
5.6%
о19
 
5.6%
н18
 
5.3%
р15
 
4.5%
т14
 
4.2%
в12
 
3.6%
с10
 
3.0%
Other values (41)155
46.0%
None
ValueCountFrequency (%)
å3
27.3%
ų3
27.3%
ž1
 
9.1%
æ1
 
9.1%
ø1
 
9.1%
É1
 
9.1%
á1
 
9.1%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.38053097
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:17.979521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile20.8
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation416.8352346
Coefficient of variation (CV)4.561532202
Kurtosis18.5048986
Mean91.38053097
Median Absolute Deviation (MAD)0
Skewness4.491775811
Sum10326
Variance173751.6128
MonotonicityNot monotonic
2022-09-05T21:51:18.065655image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
179
69.9%
213
 
11.5%
20205
 
4.4%
54
 
3.5%
44
 
3.5%
72
 
1.8%
32
 
1.8%
81
 
0.9%
121
 
0.9%
311
 
0.9%
ValueCountFrequency (%)
179
69.9%
213
 
11.5%
32
 
1.8%
44
 
3.5%
54
 
3.5%
72
 
1.8%
81
 
0.9%
121
 
0.9%
141
 
0.9%
311
 
0.9%
ValueCountFrequency (%)
20205
 
4.4%
311
 
0.9%
141
 
0.9%
121
 
0.9%
81
 
0.9%
72
 
1.8%
54
 
3.5%
44
 
3.5%
32
 
1.8%
213
11.5%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)38.7%
Missing2
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean24.53153153
Minimum1
Maximum357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:18.169651image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median8
Q323.5
95-th percentile65.5
Maximum357
Range356
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation55.06439533
Coefficient of variation (CV)2.244637489
Kurtosis25.97679321
Mean24.53153153
Median Absolute Deviation (MAD)6
Skewness4.955983477
Sum2723
Variance3032.087633
MonotonicityNot monotonic
2022-09-05T21:51:18.292948image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
112
 
10.6%
49
 
8.0%
29
 
8.0%
38
 
7.1%
58
 
7.1%
67
 
6.2%
85
 
4.4%
135
 
4.4%
233
 
2.7%
143
 
2.7%
Other values (33)42
37.2%
ValueCountFrequency (%)
112
10.6%
29
8.0%
38
7.1%
49
8.0%
58
7.1%
67
6.2%
71
 
0.9%
85
4.4%
91
 
0.9%
101
 
0.9%
ValueCountFrequency (%)
3571
0.9%
3221
0.9%
3211
0.9%
891
0.9%
861
0.9%
711
0.9%
601
0.9%
591
0.9%
551
0.9%
531
0.9%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
regular
111 
insignificant_special
 
1
significant_special
 
1

Length

Max length21
Median length7
Mean length7.230088496
Min length7

Characters and Unicode

Total characters817
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st rowregular
2nd rowinsignificant_special
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular111
98.2%
insignificant_special1
 
0.9%
significant_special1
 
0.9%

Length

2022-09-05T21:51:18.397669image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:18.488528image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular111
98.2%
insignificant_special1
 
0.9%
significant_special1
 
0.9%

Most occurring characters

ValueCountFrequency (%)
r222
27.2%
a115
14.1%
e113
13.8%
g113
13.8%
l113
13.8%
u111
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (4)8
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter815
99.8%
Connector Punctuation2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r222
27.2%
a115
14.1%
e113
13.9%
g113
13.9%
l113
13.9%
u111
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (3)6
 
0.7%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin815
99.8%
Common2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r222
27.2%
a115
14.1%
e113
13.9%
g113
13.9%
l113
13.9%
u111
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (3)6
 
0.7%
Common
ValueCountFrequency (%)
_2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r222
27.2%
a115
14.1%
e113
13.8%
g113
13.8%
l113
13.8%
u111
13.6%
i9
 
1.1%
n5
 
0.6%
s4
 
0.5%
c4
 
0.5%
Other values (4)8
 
1.0%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-30
113 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1130
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-30
2nd row2020-12-30
3rd row2020-12-30
4th row2020-12-30
5th row2020-12-30

Common Values

ValueCountFrequency (%)
2020-12-30113
100.0%

Length

2022-09-05T21:51:18.570028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:18.650271image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-30113
100.0%

Most occurring characters

ValueCountFrequency (%)
2339
30.0%
0339
30.0%
-226
20.0%
1113
 
10.0%
3113
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number904
80.0%
Dash Punctuation226
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2339
37.5%
0339
37.5%
1113
 
12.5%
3113
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2339
30.0%
0339
30.0%
-226
20.0%
1113
 
10.0%
3113
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2339
30.0%
0339
30.0%
-226
20.0%
1113
 
10.0%
3113
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
87 
20:00
14 
12:00
 
3
10:00
 
2
18:00
 
2
Other values (4)
 
5

Length

Max length5
Median length0
Mean length1.150442478
Min length0

Characters and Unicode

Total characters130
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.7%

Sample

1st row12:00
2nd row
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
87
77.0%
20:0014
 
12.4%
12:003
 
2.7%
10:002
 
1.8%
18:002
 
1.8%
00:002
 
1.8%
08:301
 
0.9%
19:001
 
0.9%
21:451
 
0.9%

Length

2022-09-05T21:51:18.724492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:18.821840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
20:0014
53.8%
12:003
 
11.5%
10:002
 
7.7%
18:002
 
7.7%
00:002
 
7.7%
08:301
 
3.8%
19:001
 
3.8%
21:451
 
3.8%

Most occurring characters

ValueCountFrequency (%)
070
53.8%
:26
 
20.0%
218
 
13.8%
19
 
6.9%
83
 
2.3%
31
 
0.8%
91
 
0.8%
41
 
0.8%
51
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number104
80.0%
Other Punctuation26
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
070
67.3%
218
 
17.3%
19
 
8.7%
83
 
2.9%
31
 
1.0%
91
 
1.0%
41
 
1.0%
51
 
1.0%
Other Punctuation
ValueCountFrequency (%)
:26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
070
53.8%
:26
 
20.0%
218
 
13.8%
19
 
6.9%
83
 
2.3%
31
 
0.8%
91
 
0.8%
41
 
0.8%
51
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
070
53.8%
:26
 
20.0%
218
 
13.8%
19
 
6.9%
83
 
2.3%
31
 
0.8%
91
 
0.8%
41
 
0.8%
51
 
0.8%

airstamp
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-30T12:00:00+00:00
71 
2020-12-30T04:00:00+00:00
17 
2020-12-30T09:00:00+00:00
 
4
2020-12-30T17:00:00+00:00
 
4
2020-12-30T00:00:00+00:00
 
3
Other values (10)
14 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2825
Distinct characters12
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)5.3%

Sample

1st row2020-12-30T00:00:00+00:00
2nd row2020-12-30T00:00:00+00:00
3rd row2020-12-30T00:00:00+00:00
4th row2020-12-30T02:00:00+00:00
5th row2020-12-30T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-30T12:00:00+00:0071
62.8%
2020-12-30T04:00:00+00:0017
 
15.0%
2020-12-30T09:00:00+00:004
 
3.5%
2020-12-30T17:00:00+00:004
 
3.5%
2020-12-30T00:00:00+00:003
 
2.7%
2020-12-30T02:00:00+00:002
 
1.8%
2020-12-30T03:00:00+00:002
 
1.8%
2020-12-30T11:00:00+00:002
 
1.8%
2020-12-31T01:00:00+00:002
 
1.8%
2020-12-30T10:00:00+00:001
 
0.9%
Other values (5)5
 
4.4%

Length

2022-09-05T21:51:18.911326image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-30t12:00:00+00:0071
62.8%
2020-12-30t04:00:00+00:0017
 
15.0%
2020-12-30t09:00:00+00:004
 
3.5%
2020-12-30t17:00:00+00:004
 
3.5%
2020-12-30t00:00:00+00:003
 
2.7%
2020-12-30t02:00:00+00:002
 
1.8%
2020-12-30t03:00:00+00:002
 
1.8%
2020-12-30t11:00:00+00:002
 
1.8%
2020-12-31t01:00:00+00:002
 
1.8%
2020-12-30t10:00:00+00:001
 
0.9%
Other values (5)5
 
4.4%

Most occurring characters

ValueCountFrequency (%)
01272
45.0%
2413
 
14.6%
:339
 
12.0%
-226
 
8.0%
1202
 
7.2%
3117
 
4.1%
T113
 
4.0%
+113
 
4.0%
418
 
0.6%
95
 
0.2%
Other values (2)7
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2034
72.0%
Other Punctuation339
 
12.0%
Dash Punctuation226
 
8.0%
Uppercase Letter113
 
4.0%
Math Symbol113
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01272
62.5%
2413
 
20.3%
1202
 
9.9%
3117
 
5.8%
418
 
0.9%
95
 
0.2%
74
 
0.2%
53
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:339
100.0%
Dash Punctuation
ValueCountFrequency (%)
-226
100.0%
Uppercase Letter
ValueCountFrequency (%)
T113
100.0%
Math Symbol
ValueCountFrequency (%)
+113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2712
96.0%
Latin113
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01272
46.9%
2413
 
15.2%
:339
 
12.5%
-226
 
8.3%
1202
 
7.4%
3117
 
4.3%
+113
 
4.2%
418
 
0.7%
95
 
0.2%
74
 
0.1%
Latin
ValueCountFrequency (%)
T113
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2825
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01272
45.0%
2413
 
14.6%
:339
 
12.0%
-226
 
8.0%
1202
 
7.2%
3117
 
4.1%
T113
 
4.0%
+113
 
4.0%
418
 
0.6%
95
 
0.2%
Other values (2)7
 
0.2%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct42
Distinct (%)40.0%
Missing8
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean39.58095238
Minimum4
Maximum208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:19.007994image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile12
Q123
median35
Q345
95-th percentile92.4
Maximum208
Range204
Interquartile range (IQR)22

Descriptive statistics

Standard deviation28.7752501
Coefficient of variation (CV)0.7269974159
Kurtosis12.04096107
Mean39.58095238
Median Absolute Deviation (MAD)10
Skewness2.831149172
Sum4156
Variance828.0150183
MonotonicityNot monotonic
2022-09-05T21:51:19.120507image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
4521
18.6%
309
 
8.0%
205
 
4.4%
125
 
4.4%
355
 
4.4%
255
 
4.4%
244
 
3.5%
364
 
3.5%
193
 
2.7%
403
 
2.7%
Other values (32)41
36.3%
(Missing)8
 
7.1%
ValueCountFrequency (%)
41
 
0.9%
51
 
0.9%
61
 
0.9%
81
 
0.9%
101
 
0.9%
125
4.4%
131
 
0.9%
153
2.7%
171
 
0.9%
182
 
1.8%
ValueCountFrequency (%)
2081
 
0.9%
1271
 
0.9%
1203
2.7%
931
 
0.9%
901
 
0.9%
661
 
0.9%
641
 
0.9%
621
 
0.9%
611
 
0.9%
602
1.8%

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct41
Distinct (%)100.0%
Missing72
Missing (%)63.7%
Memory size1.0 KiB
<p>Despite the serious charges against him, Muccioli receives overwhelming support from the public, including many affected by the heroin crisis.</p><p><br /> </p>
 
1
<p>Game day appetizers morph into meals that score big points with the judges. The contestants must reimagine smoky barbecue takeout as a gourmet feast.</p><p><br /> </p>
 
1
<p>A festive meal means lots of leftovers. So how about glazed ham, apple pie and green bean casserole… on a sandwich? Later, Greek food gets a new life.</p><p><br /> </p>
 
1
<p>The cooks serve up a spectacular breakfast using fancy date-night leftovers from the fridge, then wow the judges with fresh takes on Italian takeout.</p><p><br /> </p>
 
1
<p>Bacon-wrapped brats and blueberry cobbler get a second look as late-night snacks, and duck confit and cassoulet evolve into entirely different dishes.</p><p><br /> </p>
 
1
Other values (36)
36 

Length

Max length556
Median length194
Mean length189.4146341
Min length84

Characters and Unicode

Total characters7766
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st row<p>A unique release of The Shocking Howe. Actors and writers of the "Comfort Zone" series will tell you how the project was created. Of course, everything is in the style of the Shocking Howe.</p>
2nd row<p>Yun Woo suffers from monochromat. In his eyes, everything is in the shades of gray colors. On the first day at Sangsang High School, Yeon Woo gets to meet new classmates. One of them is Go Yoo Han who dreams of becoming a K-pop artist. When Yoo Han takes off his mask, Yun Woo starts to see the colors.</p>
3rd row<p>Amos and Clarissa are trapped in a collapsed building. Naomi contends with her old family. Holden assembles a new crew on the Roci. Alex and Bobbie make a dangerous discovery in the Belt.</p>
4th row<p>Surprise! Here's one last random episode to round out the season. Check out the hi-jinks the gals got up to that didn't make the episodes!</p>
5th row<p>Believing the Allspark destroyed, Megatron plans to flee the dying planet — but at great cost. Elita's plan to free some prisoners hits a snag.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p>Despite the serious charges against him, Muccioli receives overwhelming support from the public, including many affected by the heroin crisis.</p><p><br /> </p>1
 
0.9%
<p>Game day appetizers morph into meals that score big points with the judges. The contestants must reimagine smoky barbecue takeout as a gourmet feast.</p><p><br /> </p>1
 
0.9%
<p>A festive meal means lots of leftovers. So how about glazed ham, apple pie and green bean casserole… on a sandwich? Later, Greek food gets a new life.</p><p><br /> </p>1
 
0.9%
<p>The cooks serve up a spectacular breakfast using fancy date-night leftovers from the fridge, then wow the judges with fresh takes on Italian takeout.</p><p><br /> </p>1
 
0.9%
<p>Bacon-wrapped brats and blueberry cobbler get a second look as late-night snacks, and duck confit and cassoulet evolve into entirely different dishes.</p><p><br /> </p>1
 
0.9%
<p>Potluck castoffs return with a vengeance as sinful desserts before the challengers tackle chilled Chinese takeout, including egg rolls and chow mein.</p><p><br /> </p>1
 
0.9%
<p>The cooks use food from a children's party to make cocktails and an indulgent brunch. Mexican dishes are remade into gnocchi, dumplings and more.</p><p><br /> </p>1
 
0.9%
<p>After creating a "flavor bomb" from notoriously bland foods like rice and toast, the competitors take on a new challenge: transforming Thai takeout.</p>1
 
0.9%
<p>Cheap heroin begins to flood Italy. With the government unable to deal with the damage, Vincenzo Muccioli opens a commune to treat addicted youth.</p><p><br /> </p>1
 
0.9%
<p>As Muccioli's fame and power grow, San Patrignano also expands beyond his immediate control. The commune struggles to deal with the AIDS epidemic.</p><p><br /> </p>1
 
0.9%
Other values (31)31
27.4%
(Missing)72
63.7%

Length

2022-09-05T21:51:19.236413image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the84
 
6.7%
to42
 
3.4%
and34
 
2.7%
a32
 
2.6%
of22
 
1.8%
22
 
1.8%
p21
 
1.7%
in16
 
1.3%
with13
 
1.0%
from12
 
1.0%
Other values (700)953
76.2%

Most occurring characters

ValueCountFrequency (%)
1189
15.3%
e738
 
9.5%
t487
 
6.3%
a467
 
6.0%
o437
 
5.6%
s432
 
5.6%
n377
 
4.9%
i366
 
4.7%
r359
 
4.6%
h289
 
3.7%
Other values (61)2625
33.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5745
74.0%
Space Separator1210
 
15.6%
Math Symbol290
 
3.7%
Other Punctuation257
 
3.3%
Uppercase Letter227
 
2.9%
Decimal Number21
 
0.3%
Dash Punctuation16
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e738
12.8%
t487
 
8.5%
a467
 
8.1%
o437
 
7.6%
s432
 
7.5%
n377
 
6.6%
i366
 
6.4%
r359
 
6.2%
h289
 
5.0%
p246
 
4.3%
Other values (16)1547
26.9%
Uppercase Letter
ValueCountFrequency (%)
A40
17.6%
T24
 
10.6%
M18
 
7.9%
C16
 
7.0%
S14
 
6.2%
I12
 
5.3%
L10
 
4.4%
H10
 
4.4%
W9
 
4.0%
R9
 
4.0%
Other values (13)65
28.6%
Other Punctuation
ValueCountFrequency (%)
/83
32.3%
.80
31.1%
,51
19.8%
'20
 
7.8%
"12
 
4.7%
!4
 
1.6%
?3
 
1.2%
:2
 
0.8%
;1
 
0.4%
1
 
0.4%
Decimal Number
ValueCountFrequency (%)
27
33.3%
07
33.3%
53
14.3%
12
 
9.5%
61
 
4.8%
31
 
4.8%
Space Separator
ValueCountFrequency (%)
1189
98.3%
 21
 
1.7%
Math Symbol
ValueCountFrequency (%)
<145
50.0%
>145
50.0%
Dash Punctuation
ValueCountFrequency (%)
-12
75.0%
4
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5972
76.9%
Common1794
 
23.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e738
12.4%
t487
 
8.2%
a467
 
7.8%
o437
 
7.3%
s432
 
7.2%
n377
 
6.3%
i366
 
6.1%
r359
 
6.0%
h289
 
4.8%
p246
 
4.1%
Other values (39)1774
29.7%
Common
ValueCountFrequency (%)
1189
66.3%
<145
 
8.1%
>145
 
8.1%
/83
 
4.6%
.80
 
4.5%
,51
 
2.8%
 21
 
1.2%
'20
 
1.1%
-12
 
0.7%
"12
 
0.7%
Other values (12)36
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7740
99.7%
None21
 
0.3%
Punctuation5
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1189
15.4%
e738
 
9.5%
t487
 
6.3%
a467
 
6.0%
o437
 
5.6%
s432
 
5.6%
n377
 
4.9%
i366
 
4.7%
r359
 
4.6%
h289
 
3.7%
Other values (58)2599
33.6%
None
ValueCountFrequency (%)
 21
100.0%
Punctuation
ValueCountFrequency (%)
4
80.0%
1
 
20.0%

rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct9
Distinct (%)52.9%
Missing96
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean7.576470588
Minimum6
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:19.329378image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6.8
Q17
median7
Q38
95-th percentile9.12
Maximum10
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9397668672
Coefficient of variation (CV)0.1240375523
Kurtosis1.629259558
Mean7.576470588
Median Absolute Deviation (MAD)0.7
Skewness1.024451755
Sum128.8
Variance0.8831617647
MonotonicityNot monotonic
2022-09-05T21:51:19.425064image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
78
 
7.1%
7.82
 
1.8%
101
 
0.9%
8.91
 
0.9%
8.41
 
0.9%
7.71
 
0.9%
81
 
0.9%
8.21
 
0.9%
61
 
0.9%
(Missing)96
85.0%
ValueCountFrequency (%)
61
 
0.9%
78
7.1%
7.71
 
0.9%
7.82
 
1.8%
81
 
0.9%
8.21
 
0.9%
8.41
 
0.9%
8.91
 
0.9%
101
 
0.9%
ValueCountFrequency (%)
101
 
0.9%
8.91
 
0.9%
8.41
 
0.9%
8.21
 
0.9%
81
 
0.9%
7.82
 
1.8%
7.71
 
0.9%
78
7.1%
61
 
0.9%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct43
Distinct (%)100.0%
Missing70
Missing (%)61.9%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/360/901425.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/291/728235.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/291/728431.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/291/728228.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/291/728229.jpg
 
1
Other values (38)
38 

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters3096
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/360/901425.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/322/807322.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/292/731145.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/291/728334.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/735209.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/360/901425.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728235.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728431.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728228.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728229.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728230.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728231.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728232.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728233.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728234.jpg1
 
0.9%
Other values (33)33
29.2%
(Missing)70
61.9%

Length

2022-09-05T21:51:19.515853image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/360/901425.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728223.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/292/731145.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728334.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/294/735209.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/292/731116.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/293/734753.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728295.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728220.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/medium_landscape/291/728221.jpg1
 
2.3%
Other values (33)33
76.7%

Most occurring characters

ValueCountFrequency (%)
/301
 
9.7%
a258
 
8.3%
t215
 
6.9%
s215
 
6.9%
m215
 
6.9%
p172
 
5.6%
e172
 
5.6%
i129
 
4.2%
c129
 
4.2%
.129
 
4.2%
Other values (22)1161
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2193
70.8%
Other Punctuation473
 
15.3%
Decimal Number387
 
12.5%
Connector Punctuation43
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a258
11.8%
t215
9.8%
s215
9.8%
m215
9.8%
p172
 
7.8%
e172
 
7.8%
i129
 
5.9%
c129
 
5.9%
d129
 
5.9%
l86
 
3.9%
Other values (8)473
21.6%
Decimal Number
ValueCountFrequency (%)
2115
29.7%
153
13.7%
748
12.4%
946
 
11.9%
841
 
10.6%
331
 
8.0%
416
 
4.1%
014
 
3.6%
513
 
3.4%
610
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/301
63.6%
.129
27.3%
:43
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2193
70.8%
Common903
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a258
11.8%
t215
9.8%
s215
9.8%
m215
9.8%
p172
 
7.8%
e172
 
7.8%
i129
 
5.9%
c129
 
5.9%
d129
 
5.9%
l86
 
3.9%
Other values (8)473
21.6%
Common
ValueCountFrequency (%)
/301
33.3%
.129
14.3%
2115
 
12.7%
153
 
5.9%
748
 
5.3%
946
 
5.1%
_43
 
4.8%
:43
 
4.8%
841
 
4.5%
331
 
3.4%
Other values (4)53
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3096
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/301
 
9.7%
a258
 
8.3%
t215
 
6.9%
s215
 
6.9%
m215
 
6.9%
p172
 
5.6%
e172
 
5.6%
i129
 
4.2%
c129
 
4.2%
.129
 
4.2%
Other values (22)1161
37.5%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct43
Distinct (%)100.0%
Missing70
Missing (%)61.9%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/360/901425.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/291/728235.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/291/728431.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/291/728228.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/291/728229.jpg
 
1
Other values (38)
38 

Length

Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

Total characters3182
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/360/901425.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/322/807322.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/292/731145.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/291/728334.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/735209.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/360/901425.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728235.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728431.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728228.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728229.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728230.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728231.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728232.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728233.jpg1
 
0.9%
https://static.tvmaze.com/uploads/images/original_untouched/291/728234.jpg1
 
0.9%
Other values (33)33
29.2%
(Missing)70
61.9%

Length

2022-09-05T21:51:19.600199image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/360/901425.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728223.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/292/731145.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728334.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/294/735209.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/292/731116.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/293/734753.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728295.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728220.jpg1
 
2.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/728221.jpg1
 
2.3%
Other values (33)33
76.7%

Most occurring characters

ValueCountFrequency (%)
/301
 
9.5%
t258
 
8.1%
a215
 
6.8%
s172
 
5.4%
o172
 
5.4%
i172
 
5.4%
m129
 
4.1%
u129
 
4.1%
e129
 
4.1%
g129
 
4.1%
Other values (23)1376
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2279
71.6%
Other Punctuation473
 
14.9%
Decimal Number387
 
12.2%
Connector Punctuation43
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t258
 
11.3%
a215
 
9.4%
s172
 
7.5%
o172
 
7.5%
i172
 
7.5%
m129
 
5.7%
u129
 
5.7%
e129
 
5.7%
g129
 
5.7%
c129
 
5.7%
Other values (9)645
28.3%
Decimal Number
ValueCountFrequency (%)
2115
29.7%
153
13.7%
748
12.4%
946
 
11.9%
841
 
10.6%
331
 
8.0%
416
 
4.1%
014
 
3.6%
513
 
3.4%
610
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/301
63.6%
.129
27.3%
:43
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2279
71.6%
Common903
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t258
 
11.3%
a215
 
9.4%
s172
 
7.5%
o172
 
7.5%
i172
 
7.5%
m129
 
5.7%
u129
 
5.7%
e129
 
5.7%
g129
 
5.7%
c129
 
5.7%
Other values (9)645
28.3%
Common
ValueCountFrequency (%)
/301
33.3%
.129
14.3%
2115
 
12.7%
153
 
5.9%
748
 
5.3%
946
 
5.1%
_43
 
4.8%
:43
 
4.8%
841
 
4.5%
331
 
3.4%
Other values (4)53
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII3182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/301
 
9.5%
t258
 
8.1%
a215
 
6.8%
s172
 
5.4%
o172
 
5.4%
i172
 
5.4%
m129
 
4.1%
u129
 
4.1%
e129
 
4.1%
g129
 
4.1%
Other values (23)1376
43.2%

_links.self.href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2179615
 
1
https://api.tvmaze.com/episodes/1958576
 
1
https://api.tvmaze.com/episodes/1995753
 
1
https://api.tvmaze.com/episodes/1995752
 
1
https://api.tvmaze.com/episodes/1995386
 
1
Other values (108)
108 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4407
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2179615
2nd rowhttps://api.tvmaze.com/episodes/2001718
3rd rowhttps://api.tvmaze.com/episodes/1987721
4th rowhttps://api.tvmaze.com/episodes/2386111
5th rowhttps://api.tvmaze.com/episodes/2095630

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21796151
 
0.9%
https://api.tvmaze.com/episodes/19585761
 
0.9%
https://api.tvmaze.com/episodes/19957531
 
0.9%
https://api.tvmaze.com/episodes/19957521
 
0.9%
https://api.tvmaze.com/episodes/19953861
 
0.9%
https://api.tvmaze.com/episodes/19957471
 
0.9%
https://api.tvmaze.com/episodes/19957461
 
0.9%
https://api.tvmaze.com/episodes/19957451
 
0.9%
https://api.tvmaze.com/episodes/19957441
 
0.9%
https://api.tvmaze.com/episodes/19957431
 
0.9%
Other values (103)103
91.2%

Length

2022-09-05T21:51:19.681168image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/21796151
 
0.9%
https://api.tvmaze.com/episodes/20017181
 
0.9%
https://api.tvmaze.com/episodes/19877211
 
0.9%
https://api.tvmaze.com/episodes/23861111
 
0.9%
https://api.tvmaze.com/episodes/20956301
 
0.9%
https://api.tvmaze.com/episodes/19936591
 
0.9%
https://api.tvmaze.com/episodes/20963041
 
0.9%
https://api.tvmaze.com/episodes/23244251
 
0.9%
https://api.tvmaze.com/episodes/23244261
 
0.9%
https://api.tvmaze.com/episodes/19986031
 
0.9%
Other values (103)103
91.2%

Most occurring characters

ValueCountFrequency (%)
/452
 
10.3%
p339
 
7.7%
s339
 
7.7%
e339
 
7.7%
t339
 
7.7%
o226
 
5.1%
a226
 
5.1%
i226
 
5.1%
.226
 
5.1%
m226
 
5.1%
Other values (16)1469
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2825
64.1%
Other Punctuation791
 
17.9%
Decimal Number791
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p339
12.0%
s339
12.0%
e339
12.0%
t339
12.0%
o226
8.0%
a226
8.0%
i226
8.0%
m226
8.0%
h113
 
4.0%
d113
 
4.0%
Other values (3)339
12.0%
Decimal Number
ValueCountFrequency (%)
9142
18.0%
1123
15.5%
299
12.5%
773
9.2%
573
9.2%
068
8.6%
658
7.3%
457
7.2%
854
 
6.8%
344
 
5.6%
Other Punctuation
ValueCountFrequency (%)
/452
57.1%
.226
28.6%
:113
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2825
64.1%
Common1582
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/452
28.6%
.226
14.3%
9142
 
9.0%
1123
 
7.8%
:113
 
7.1%
299
 
6.3%
773
 
4.6%
573
 
4.6%
068
 
4.3%
658
 
3.7%
Other values (3)155
 
9.8%
Latin
ValueCountFrequency (%)
p339
12.0%
s339
12.0%
e339
12.0%
t339
12.0%
o226
8.0%
a226
8.0%
i226
8.0%
m226
8.0%
h113
 
4.0%
d113
 
4.0%
Other values (3)339
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/452
 
10.3%
p339
 
7.7%
s339
 
7.7%
e339
 
7.7%
t339
 
7.7%
o226
 
5.1%
a226
 
5.1%
i226
 
5.1%
.226
 
5.1%
m226
 
5.1%
Other values (16)1469
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48521.50442
Minimum1825
Maximum62127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:19.781130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1825
5-th percentile17482.6
Q144276
median52471
Q353093
95-th percentile61556
Maximum62127
Range60302
Interquartile range (IQR)8817

Descriptive statistics

Standard deviation12210.19027
Coefficient of variation (CV)0.2516449236
Kurtosis5.800091504
Mean48521.50442
Median Absolute Deviation (MAD)3118
Skewness-2.296103613
Sum5482930
Variance149088746.5
MonotonicityNot monotonic
2022-09-05T21:51:19.903496image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
526158
 
7.1%
438906
 
5.3%
615566
 
5.3%
423876
 
5.3%
527085
 
4.4%
521043
 
2.7%
152502
 
1.8%
472262
 
1.8%
525242
 
1.8%
529312
 
1.8%
Other values (62)71
62.8%
ValueCountFrequency (%)
18251
0.9%
22661
0.9%
25041
0.9%
64411
0.9%
152502
1.8%
189711
0.9%
283461
0.9%
306061
0.9%
339441
0.9%
340601
0.9%
ValueCountFrequency (%)
621271
 
0.9%
617551
 
0.9%
615566
5.3%
612472
 
1.8%
605081
 
0.9%
601611
 
0.9%
586892
 
1.8%
586451
 
0.9%
584261
 
0.9%
574781
 
0.9%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://www.tvmaze.com/shows/52615/best-leftovers-ever
 
8
https://www.tvmaze.com/shows/43890/equinox
 
6
https://www.tvmaze.com/shows/61556/unsolved-cases-of-kung-fu-portrait-of-beauty
 
6
https://www.tvmaze.com/shows/42387/transformers-war-for-cybertron-trilogy
 
6
https://www.tvmaze.com/shows/52708/sanpa-luci-e-tenebre-di-san-patrignano
 
5
Other values (67)
82 

Length

Max length79
Median length59
Mean length54.47787611
Min length39

Characters and Unicode

Total characters6156
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.9%

Sample

1st rowhttps://www.tvmaze.com/shows/49630/kontakty
2nd rowhttps://www.tvmaze.com/shows/51510/zona-komforta
3rd rowhttps://www.tvmaze.com/shows/52499/passaziry
4th rowhttps://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu
5th rowhttps://www.tvmaze.com/shows/49652/yi-nian-yong-heng

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/52615/best-leftovers-ever8
 
7.1%
https://www.tvmaze.com/shows/43890/equinox6
 
5.3%
https://www.tvmaze.com/shows/61556/unsolved-cases-of-kung-fu-portrait-of-beauty6
 
5.3%
https://www.tvmaze.com/shows/42387/transformers-war-for-cybertron-trilogy6
 
5.3%
https://www.tvmaze.com/shows/52708/sanpa-luci-e-tenebre-di-san-patrignano5
 
4.4%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love3
 
2.7%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
1.8%
https://www.tvmaze.com/shows/47226/arashis-diary-voyage2
 
1.8%
https://www.tvmaze.com/shows/52524/forever-love2
 
1.8%
https://www.tvmaze.com/shows/52931/10-bin-adim2
 
1.8%
Other values (62)71
62.8%

Length

2022-09-05T21:51:20.025113image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/52615/best-leftovers-ever8
 
7.1%
https://www.tvmaze.com/shows/61556/unsolved-cases-of-kung-fu-portrait-of-beauty6
 
5.3%
https://www.tvmaze.com/shows/42387/transformers-war-for-cybertron-trilogy6
 
5.3%
https://www.tvmaze.com/shows/43890/equinox6
 
5.3%
https://www.tvmaze.com/shows/52708/sanpa-luci-e-tenebre-di-san-patrignano5
 
4.4%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love3
 
2.7%
https://www.tvmaze.com/shows/58689/my-supernatural-power2
 
1.8%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
1.8%
https://www.tvmaze.com/shows/52421/you-complete-me2
 
1.8%
https://www.tvmaze.com/shows/52400/dream-detective2
 
1.8%
Other values (62)71
62.8%

Most occurring characters

ValueCountFrequency (%)
/565
 
9.2%
t478
 
7.8%
w475
 
7.7%
s465
 
7.6%
o376
 
6.1%
e344
 
5.6%
-277
 
4.5%
h269
 
4.4%
m267
 
4.3%
a262
 
4.3%
Other values (30)2378
38.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4398
71.4%
Other Punctuation904
 
14.7%
Decimal Number577
 
9.4%
Dash Punctuation277
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t478
10.9%
w475
10.8%
s465
10.6%
o376
 
8.5%
e344
 
7.8%
h269
 
6.1%
m267
 
6.1%
a262
 
6.0%
c156
 
3.5%
r154
 
3.5%
Other values (16)1152
26.2%
Decimal Number
ValueCountFrequency (%)
5105
18.2%
279
13.7%
469
12.0%
659
10.2%
151
8.8%
049
8.5%
846
8.0%
743
7.5%
341
 
7.1%
935
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/565
62.5%
.226
 
25.0%
:113
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-277
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4398
71.4%
Common1758
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t478
10.9%
w475
10.8%
s465
10.6%
o376
 
8.5%
e344
 
7.8%
h269
 
6.1%
m267
 
6.1%
a262
 
6.0%
c156
 
3.5%
r154
 
3.5%
Other values (16)1152
26.2%
Common
ValueCountFrequency (%)
/565
32.1%
-277
15.8%
.226
 
12.9%
:113
 
6.4%
5105
 
6.0%
279
 
4.5%
469
 
3.9%
659
 
3.4%
151
 
2.9%
049
 
2.8%
Other values (4)165
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII6156
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/565
 
9.2%
t478
 
7.8%
w475
 
7.7%
s465
 
7.6%
o376
 
6.1%
e344
 
5.6%
-277
 
4.5%
h269
 
4.4%
m267
 
4.3%
a262
 
4.3%
Other values (30)2378
38.6%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Best Leftovers Ever!
 
8
Equinox
 
6
Unsolved Cases of Kung Fu: Portrait of Beauty
 
6
Transformers: War for Cybertron Trilogy
 
6
SanPa: Luci e tenebre di San Patrignano
 
5
Other values (67)
82 

Length

Max length45
Median length25
Mean length19.92035398
Min length5

Characters and Unicode

Total characters2251
Distinct characters100
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.9%

Sample

1st rowКонтакты
2nd rowЗона комфорта
3rd rowПассажиры
4th rowXian Feng Jian Yu Lu
5th rowYi Nian Yong Heng

Common Values

ValueCountFrequency (%)
Best Leftovers Ever!8
 
7.1%
Equinox6
 
5.3%
Unsolved Cases of Kung Fu: Portrait of Beauty6
 
5.3%
Transformers: War for Cybertron Trilogy6
 
5.3%
SanPa: Luci e tenebre di San Patrignano5
 
4.4%
Twisted Fate of Love3
 
2.7%
The Young Turks2
 
1.8%
Arashi's Diary: Voyage2
 
1.8%
Forever Love2
 
1.8%
10 Bin Adim2
 
1.8%
Other values (62)71
62.8%

Length

2022-09-05T21:51:20.146474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of20
 
5.1%
best10
 
2.6%
the10
 
2.6%
leftovers8
 
2.1%
ever8
 
2.1%
unsolved6
 
1.5%
for6
 
1.5%
love6
 
1.5%
my6
 
1.5%
cases6
 
1.5%
Other values (177)304
77.9%

Most occurring characters

ValueCountFrequency (%)
277
 
12.3%
e204
 
9.1%
r140
 
6.2%
o135
 
6.0%
n119
 
5.3%
a119
 
5.3%
i106
 
4.7%
t97
 
4.3%
s90
 
4.0%
u66
 
2.9%
Other values (90)898
39.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1573
69.9%
Uppercase Letter341
 
15.1%
Space Separator277
 
12.3%
Other Punctuation44
 
2.0%
Decimal Number16
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e204
13.0%
r140
 
8.9%
o135
 
8.6%
n119
 
7.6%
a119
 
7.6%
i106
 
6.7%
t97
 
6.2%
s90
 
5.7%
u66
 
4.2%
y46
 
2.9%
Other values (42)451
28.7%
Uppercase Letter
ValueCountFrequency (%)
T32
 
9.4%
L31
 
9.1%
S29
 
8.5%
B23
 
6.7%
C23
 
6.7%
P22
 
6.5%
F19
 
5.6%
E19
 
5.6%
D16
 
4.7%
Y15
 
4.4%
Other values (25)112
32.8%
Other Punctuation
ValueCountFrequency (%)
:26
59.1%
!8
 
18.2%
'7
 
15.9%
?1
 
2.3%
.1
 
2.3%
,1
 
2.3%
Decimal Number
ValueCountFrequency (%)
25
31.2%
05
31.2%
13
18.8%
51
 
6.2%
71
 
6.2%
31
 
6.2%
Space Separator
ValueCountFrequency (%)
277
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1786
79.3%
Common337
 
15.0%
Cyrillic128
 
5.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e204
 
11.4%
r140
 
7.8%
o135
 
7.6%
n119
 
6.7%
a119
 
6.7%
i106
 
5.9%
t97
 
5.4%
s90
 
5.0%
u66
 
3.7%
y46
 
2.6%
Other values (41)664
37.2%
Cyrillic
ValueCountFrequency (%)
о14
 
10.9%
а12
 
9.4%
и11
 
8.6%
т9
 
7.0%
р8
 
6.2%
н8
 
6.2%
к7
 
5.5%
с6
 
4.7%
е6
 
4.7%
з4
 
3.1%
Other values (26)43
33.6%
Common
ValueCountFrequency (%)
277
82.2%
:26
 
7.7%
!8
 
2.4%
'7
 
2.1%
25
 
1.5%
05
 
1.5%
13
 
0.9%
?1
 
0.3%
.1
 
0.3%
51
 
0.3%
Other values (3)3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2122
94.3%
Cyrillic128
 
5.7%
None1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
277
 
13.1%
e204
 
9.6%
r140
 
6.6%
o135
 
6.4%
n119
 
5.6%
a119
 
5.6%
i106
 
5.0%
t97
 
4.6%
s90
 
4.2%
u66
 
3.1%
Other values (53)769
36.2%
Cyrillic
ValueCountFrequency (%)
о14
 
10.9%
а12
 
9.4%
и11
 
8.6%
т9
 
7.0%
р8
 
6.2%
н8
 
6.2%
к7
 
5.5%
с6
 
4.7%
е6
 
4.7%
з4
 
3.1%
Other values (26)43
33.6%
None
ValueCountFrequency (%)
ė1
100.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Scripted
54 
Animation
16 
Reality
11 
Documentary
11 
Talk Show
Other values (4)
12 

Length

Max length11
Median length9
Mean length8.283185841
Min length4

Characters and Unicode

Total characters936
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGame Show
2nd rowScripted
3rd rowScripted
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted54
47.8%
Animation16
 
14.2%
Reality11
 
9.7%
Documentary11
 
9.7%
Talk Show9
 
8.0%
Variety4
 
3.5%
Game Show3
 
2.7%
Sports3
 
2.7%
News2
 
1.8%

Length

2022-09-05T21:51:20.251783image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:20.361809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted54
43.2%
animation16
 
12.8%
show12
 
9.6%
reality11
 
8.8%
documentary11
 
8.8%
talk9
 
7.2%
variety4
 
3.2%
game3
 
2.4%
sports3
 
2.4%
news2
 
1.6%

Most occurring characters

ValueCountFrequency (%)
i101
10.8%
t99
10.6%
e85
 
9.1%
r72
 
7.7%
S69
 
7.4%
c65
 
6.9%
p57
 
6.1%
a54
 
5.8%
d54
 
5.8%
n43
 
4.6%
Other values (17)237
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter799
85.4%
Uppercase Letter125
 
13.4%
Space Separator12
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i101
12.6%
t99
12.4%
e85
10.6%
r72
9.0%
c65
8.1%
p57
7.1%
a54
6.8%
d54
6.8%
n43
 
5.4%
o42
 
5.3%
Other values (8)127
15.9%
Uppercase Letter
ValueCountFrequency (%)
S69
55.2%
A16
 
12.8%
R11
 
8.8%
D11
 
8.8%
T9
 
7.2%
V4
 
3.2%
G3
 
2.4%
N2
 
1.6%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin924
98.7%
Common12
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
i101
10.9%
t99
10.7%
e85
 
9.2%
r72
 
7.8%
S69
 
7.5%
c65
 
7.0%
p57
 
6.2%
a54
 
5.8%
d54
 
5.8%
n43
 
4.7%
Other values (16)225
24.4%
Common
ValueCountFrequency (%)
12
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i101
10.8%
t99
10.6%
e85
 
9.1%
r72
 
7.7%
S69
 
7.4%
c65
 
6.9%
p57
 
6.1%
a54
 
5.8%
d54
 
5.8%
n43
 
4.6%
Other values (17)237
25.3%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)17.0%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
Chinese
34 
English
32 
Russian
Danish
Korean
Other values (14)
27 

Length

Max length10
Median length7
Mean length6.982142857
Min length4

Characters and Unicode

Total characters782
Distinct characters34
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)6.2%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Chinese34
30.1%
English32
28.3%
Russian8
 
7.1%
Danish6
 
5.3%
Korean5
 
4.4%
Italian5
 
4.4%
Arabic3
 
2.7%
Norwegian3
 
2.7%
Japanese3
 
2.7%
Ukrainian2
 
1.8%
Other values (9)11
 
9.7%

Length

2022-09-05T21:51:20.459993image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese34
30.4%
english32
28.6%
russian8
 
7.1%
danish6
 
5.4%
korean5
 
4.5%
italian5
 
4.5%
arabic3
 
2.7%
norwegian3
 
2.7%
japanese3
 
2.7%
turkish2
 
1.8%
Other values (9)11
 
9.8%

Most occurring characters

ValueCountFrequency (%)
n106
13.6%
i104
13.3%
s94
12.0%
e87
11.1%
h78
10.0%
a56
7.2%
g38
 
4.9%
l38
 
4.9%
C34
 
4.3%
E32
 
4.1%
Other values (24)115
14.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter670
85.7%
Uppercase Letter112
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n106
15.8%
i104
15.5%
s94
14.0%
e87
13.0%
h78
11.6%
a56
8.4%
g38
 
5.7%
l38
 
5.7%
r17
 
2.5%
u13
 
1.9%
Other values (9)39
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
C34
30.4%
E32
28.6%
R8
 
7.1%
D7
 
6.2%
K5
 
4.5%
I5
 
4.5%
T5
 
4.5%
J3
 
2.7%
N3
 
2.7%
A3
 
2.7%
Other values (5)7
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Latin782
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n106
13.6%
i104
13.3%
s94
12.0%
e87
11.1%
h78
10.0%
a56
7.2%
g38
 
4.9%
l38
 
4.9%
C34
 
4.3%
E32
 
4.1%
Other values (24)115
14.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII782
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n106
13.6%
i104
13.3%
s94
12.0%
e87
11.1%
h78
10.0%
a56
7.2%
g38
 
4.9%
l38
 
4.9%
C34
 
4.3%
E32
 
4.1%
Other values (24)115
14.7%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Ended
57 
Running
35 
To Be Determined
21 

Length

Max length16
Median length5
Mean length7.663716814
Min length5

Characters and Unicode

Total characters866
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Ended57
50.4%
Running35
31.0%
To Be Determined21
 
18.6%

Length

2022-09-05T21:51:20.546563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:20.632155image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ended57
36.8%
running35
22.6%
to21
 
13.5%
be21
 
13.5%
determined21
 
13.5%

Most occurring characters

ValueCountFrequency (%)
n183
21.1%
e141
16.3%
d135
15.6%
E57
 
6.6%
i56
 
6.5%
42
 
4.8%
R35
 
4.0%
u35
 
4.0%
g35
 
4.0%
T21
 
2.4%
Other values (6)126
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter669
77.3%
Uppercase Letter155
 
17.9%
Space Separator42
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n183
27.4%
e141
21.1%
d135
20.2%
i56
 
8.4%
u35
 
5.2%
g35
 
5.2%
o21
 
3.1%
t21
 
3.1%
r21
 
3.1%
m21
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
E57
36.8%
R35
22.6%
T21
 
13.5%
B21
 
13.5%
D21
 
13.5%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin824
95.2%
Common42
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n183
22.2%
e141
17.1%
d135
16.4%
E57
 
6.9%
i56
 
6.8%
R35
 
4.2%
u35
 
4.2%
g35
 
4.2%
T21
 
2.5%
o21
 
2.5%
Other values (5)105
12.7%
Common
ValueCountFrequency (%)
42
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII866
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n183
21.1%
e141
16.3%
d135
15.6%
E57
 
6.6%
i56
 
6.5%
42
 
4.8%
R35
 
4.0%
u35
 
4.0%
g35
 
4.0%
T21
 
2.4%
Other values (6)126
14.5%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct19
Distinct (%)30.2%
Missing50
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean40.96825397
Minimum4
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:20.725818image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile12
Q124
median38
Q345
95-th percentile117
Maximum120
Range116
Interquartile range (IQR)21

Descriptive statistics

Standard deviation26.75333459
Coefficient of variation (CV)0.6530259895
Kurtosis2.998755383
Mean40.96825397
Median Absolute Deviation (MAD)8
Skewness1.678845303
Sum2581
Variance715.7409114
MonotonicityNot monotonic
2022-09-05T21:51:20.823305image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4519
 
16.8%
3010
 
8.8%
207
 
6.2%
1204
 
3.5%
253
 
2.7%
603
 
2.7%
382
 
1.8%
402
 
1.8%
902
 
1.8%
122
 
1.8%
Other values (9)9
 
8.0%
(Missing)50
44.2%
ValueCountFrequency (%)
41
 
0.9%
51
 
0.9%
81
 
0.9%
122
 
1.8%
151
 
0.9%
181
 
0.9%
191
 
0.9%
207
6.2%
231
 
0.9%
253
2.7%
ValueCountFrequency (%)
1204
 
3.5%
902
 
1.8%
661
 
0.9%
603
 
2.7%
4519
16.8%
402
 
1.8%
382
 
1.8%
331
 
0.9%
3010
8.8%
253
 
2.7%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)31.5%
Missing5
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean37.62037037
Minimum4
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:20.921235image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile11.35
Q125
median36
Q345
95-th percentile76.65
Maximum120
Range116
Interquartile range (IQR)20

Descriptive statistics

Standard deviation22.55614701
Coefficient of variation (CV)0.5995726993
Kurtosis4.172862427
Mean37.62037037
Median Absolute Deviation (MAD)10
Skewness1.685468217
Sum4063
Variance508.7797681
MonotonicityNot monotonic
2022-09-05T21:51:21.030847image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4518
15.9%
3011
 
9.7%
2510
 
8.8%
369
 
8.0%
607
 
6.2%
206
 
5.3%
466
 
5.3%
125
 
4.4%
424
 
3.5%
1203
 
2.7%
Other values (24)29
25.7%
(Missing)5
 
4.4%
ValueCountFrequency (%)
41
 
0.9%
52
 
1.8%
71
 
0.9%
91
 
0.9%
111
 
0.9%
125
4.4%
131
 
0.9%
151
 
0.9%
161
 
0.9%
171
 
0.9%
ValueCountFrequency (%)
1203
2.7%
1101
 
0.9%
901
 
0.9%
771
 
0.9%
761
 
0.9%
607
6.2%
581
 
0.9%
561
 
0.9%
551
 
0.9%
466
5.3%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct53
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2020-12-30
35 
2020-07-30
 
6
2020-12-16
 
5
2020-11-23
 
3
2020-12-08
 
3
Other values (48)
61 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1130
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)33.6%

Sample

1st row2019-04-03
2nd row2020-10-22
3rd row2020-12-24
4th row2020-07-11
5th row2020-08-12

Common Values

ValueCountFrequency (%)
2020-12-3035
31.0%
2020-07-306
 
5.3%
2020-12-165
 
4.4%
2020-11-233
 
2.7%
2020-12-083
 
2.7%
2020-11-183
 
2.7%
2020-12-143
 
2.7%
2020-12-243
 
2.7%
2019-01-172
 
1.8%
2020-12-022
 
1.8%
Other values (43)48
42.5%

Length

2022-09-05T21:51:21.128051image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-3035
31.0%
2020-07-306
 
5.3%
2020-12-165
 
4.4%
2020-11-233
 
2.7%
2020-12-083
 
2.7%
2020-11-183
 
2.7%
2020-12-143
 
2.7%
2020-12-243
 
2.7%
2020-12-272
 
1.8%
2013-12-242
 
1.8%
Other values (43)48
42.5%

Most occurring characters

ValueCountFrequency (%)
2295
26.1%
0289
25.6%
-226
20.0%
1164
14.5%
358
 
5.1%
925
 
2.2%
820
 
1.8%
719
 
1.7%
416
 
1.4%
612
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number904
80.0%
Dash Punctuation226
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2295
32.6%
0289
32.0%
1164
18.1%
358
 
6.4%
925
 
2.8%
820
 
2.2%
719
 
2.1%
416
 
1.8%
612
 
1.3%
56
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2295
26.1%
0289
25.6%
-226
20.0%
1164
14.5%
358
 
5.1%
925
 
2.2%
820
 
1.8%
719
 
1.7%
416
 
1.4%
612
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII1130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2295
26.1%
0289
25.6%
-226
20.0%
1164
14.5%
358
 
5.1%
925
 
2.2%
820
 
1.8%
719
 
1.7%
416
 
1.4%
612
 
1.1%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct21
Distinct (%)36.8%
Missing56
Missing (%)49.6%
Memory size1.0 KiB
2020-12-30
12 
2021-01-07
10 
2021-07-29
2021-01-05
2021-01-15
 
2
Other values (16)
23 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters570
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)15.8%

Sample

1st row2022-03-02
2nd row2022-05-27
3rd row2021-01-20
4th row2021-01-06
5th row2021-01-07

Common Values

ValueCountFrequency (%)
2020-12-3012
 
10.6%
2021-01-0710
 
8.8%
2021-07-296
 
5.3%
2021-01-054
 
3.5%
2021-01-152
 
1.8%
2021-01-202
 
1.8%
2021-01-092
 
1.8%
2021-01-142
 
1.8%
2021-01-272
 
1.8%
2022-01-012
 
1.8%
Other values (11)13
 
11.5%
(Missing)56
49.6%

Length

2022-09-05T21:51:21.218729image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-3012
21.1%
2021-01-0710
17.5%
2021-07-296
10.5%
2021-01-054
 
7.0%
2021-01-272
 
3.5%
2021-02-282
 
3.5%
2022-01-012
 
3.5%
2021-02-032
 
3.5%
2021-01-142
 
3.5%
2021-01-092
 
3.5%
Other values (11)13
22.8%

Most occurring characters

ValueCountFrequency (%)
2152
26.7%
0151
26.5%
-114
20.0%
192
16.1%
321
 
3.7%
719
 
3.3%
98
 
1.4%
57
 
1.2%
43
 
0.5%
82
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number456
80.0%
Dash Punctuation114
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2152
33.3%
0151
33.1%
192
20.2%
321
 
4.6%
719
 
4.2%
98
 
1.8%
57
 
1.5%
43
 
0.7%
82
 
0.4%
61
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
-114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common570
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2152
26.7%
0151
26.5%
-114
20.0%
192
16.1%
321
 
3.7%
719
 
3.3%
98
 
1.4%
57
 
1.2%
43
 
0.5%
82
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII570
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2152
26.7%
0151
26.5%
-114
20.0%
192
16.1%
321
 
3.7%
719
 
3.3%
98
 
1.4%
57
 
1.2%
43
 
0.5%
82
 
0.4%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct64
Distinct (%)63.4%
Missing12
Missing (%)10.6%
Memory size1.0 KiB
https://www.netflix.com/title/81087405
https://www.netflix.com/title/81075958
 
6
https://www.netflix.com/title/81002438
 
6
https://v.qq.com/x/cover/mzc00200tyfmlws.html
 
6
https://www.netflix.com/title/81010965
 
5
Other values (59)
70 

Length

Max length250
Median length79
Mean length48.18811881
Min length18

Characters and Unicode

Total characters4867
Distinct characters75
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)48.5%

Sample

1st rowhttps://www.youtube.com/playlist?list=PLZ1FUdedsrSJubWkFFh5vKHzawzQk1mYI
2nd rowhttps://okko.tv/serial/zona-komforta
3rd rowhttps://start.ru/watch/passazhiry
4th rowhttps://v.qq.com/detail/m/mzc00200hc38s5x.html
5th rowhttps://v.qq.com/detail/w/ww18u675tfmhas6.html

Common Values

ValueCountFrequency (%)
https://www.netflix.com/title/810874058
 
7.1%
https://www.netflix.com/title/810759586
 
5.3%
https://www.netflix.com/title/810024386
 
5.3%
https://v.qq.com/x/cover/mzc00200tyfmlws.html6
 
5.3%
https://www.netflix.com/title/810109655
 
4.4%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=3
 
2.7%
https://www.bilibili.com/bangumi/media/md282339532
 
1.8%
https://www.netflix.com/title/812190732
 
1.8%
https://www.tytnetwork.com2
 
1.8%
https://www.gain.tv/t/21DN4vz5/10-bin-adim2
 
1.8%
Other values (54)59
52.2%
(Missing)12
 
10.6%

Length

2022-09-05T21:51:21.328626image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com/title/810874058
 
7.9%
https://www.netflix.com/title/810024386
 
5.9%
https://v.qq.com/x/cover/mzc00200tyfmlws.html6
 
5.9%
https://www.netflix.com/title/810759586
 
5.9%
https://www.netflix.com/title/810109655
 
5.0%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab3
 
3.0%
https://v.qq.com/detail/u/umpnsyqfu7f60se.html2
 
2.0%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.0%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html2
 
2.0%
http://www.iqiyi.com/a_19rrhvpyyp.html2
 
2.0%
Other values (54)59
58.4%

Most occurring characters

ValueCountFrequency (%)
t431
 
8.9%
/410
 
8.4%
w234
 
4.8%
.214
 
4.4%
s204
 
4.2%
e190
 
3.9%
o172
 
3.5%
m171
 
3.5%
h169
 
3.5%
i166
 
3.4%
Other values (65)2506
51.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3007
61.8%
Other Punctuation863
 
17.7%
Decimal Number598
 
12.3%
Uppercase Letter321
 
6.6%
Dash Punctuation38
 
0.8%
Math Symbol26
 
0.5%
Connector Punctuation14
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t431
14.3%
w234
 
7.8%
s204
 
6.8%
e190
 
6.3%
o172
 
5.7%
m171
 
5.7%
h169
 
5.6%
i166
 
5.5%
l164
 
5.5%
p147
 
4.9%
Other values (16)959
31.9%
Uppercase Letter
ValueCountFrequency (%)
B49
15.3%
E43
13.4%
A26
 
8.1%
L21
 
6.5%
P14
 
4.4%
D14
 
4.4%
Y14
 
4.4%
W13
 
4.0%
R11
 
3.4%
H10
 
3.1%
Other values (16)106
33.0%
Decimal Number
ValueCountFrequency (%)
0133
22.2%
899
16.6%
173
12.2%
565
10.9%
954
9.0%
443
 
7.2%
241
 
6.9%
736
 
6.0%
328
 
4.7%
626
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/410
47.5%
.214
24.8%
%111
 
12.9%
:101
 
11.7%
?14
 
1.6%
&9
 
1.0%
'2
 
0.2%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=23
88.5%
+3
 
11.5%
Dash Punctuation
ValueCountFrequency (%)
-38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3328
68.4%
Common1539
31.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t431
 
13.0%
w234
 
7.0%
s204
 
6.1%
e190
 
5.7%
o172
 
5.2%
m171
 
5.1%
h169
 
5.1%
i166
 
5.0%
l164
 
4.9%
p147
 
4.4%
Other values (42)1280
38.5%
Common
ValueCountFrequency (%)
/410
26.6%
.214
13.9%
0133
 
8.6%
%111
 
7.2%
:101
 
6.6%
899
 
6.4%
173
 
4.7%
565
 
4.2%
954
 
3.5%
443
 
2.8%
Other values (13)236
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t431
 
8.9%
/410
 
8.4%
w234
 
4.8%
.214
 
4.4%
s204
 
4.2%
e190
 
3.9%
o172
 
3.5%
m171
 
3.5%
h169
 
3.5%
i166
 
3.4%
Other values (65)2506
51.5%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
82 
20:00
14 
12:30
 
6
19:00
 
3
10:00
 
2
Other values (4)
 
6

Length

Max length5
Median length0
Mean length1.371681416
Min length0

Characters and Unicode

Total characters155
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row
2nd row
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
82
72.6%
20:0014
 
12.4%
12:306
 
5.3%
19:003
 
2.7%
10:002
 
1.8%
18:002
 
1.8%
00:002
 
1.8%
08:301
 
0.9%
20:301
 
0.9%

Length

2022-09-05T21:51:21.431012image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:21.529731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
20:0014
45.2%
12:306
19.4%
19:003
 
9.7%
10:002
 
6.5%
18:002
 
6.5%
00:002
 
6.5%
08:301
 
3.2%
20:301
 
3.2%

Most occurring characters

ValueCountFrequency (%)
076
49.0%
:31
20.0%
221
 
13.5%
113
 
8.4%
38
 
5.2%
93
 
1.9%
83
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number124
80.0%
Other Punctuation31
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
076
61.3%
221
 
16.9%
113
 
10.5%
38
 
6.5%
93
 
2.4%
83
 
2.4%
Other Punctuation
ValueCountFrequency (%)
:31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common155
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
076
49.0%
:31
20.0%
221
 
13.5%
113
 
8.4%
38
 
5.2%
93
 
1.9%
83
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
076
49.0%
:31
20.0%
221
 
13.5%
113
 
8.4%
38
 
5.2%
93
 
1.9%
83
 
1.9%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size1.0 KiB

_embedded.show.rating.average
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)35.3%
Missing96
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean6.552941176
Minimum3.6
Maximum8.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:21.604462image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3.6
5-th percentile5.68
Q16.2
median6.6
Q36.6
95-th percentile8
Maximum8.8
Range5.2
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation1.02841969
Coefficient of variation (CV)0.1569401681
Kurtosis4.841969864
Mean6.552941176
Median Absolute Deviation (MAD)0.4
Skewness-0.7935217721
Sum111.4
Variance1.057647059
MonotonicityNot monotonic
2022-09-05T21:51:21.692276image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6.66
 
5.3%
6.26
 
5.3%
7.22
 
1.8%
7.81
 
0.9%
8.81
 
0.9%
3.61
 
0.9%
(Missing)96
85.0%
ValueCountFrequency (%)
3.61
 
0.9%
6.26
5.3%
6.66
5.3%
7.22
 
1.8%
7.81
 
0.9%
8.81
 
0.9%
ValueCountFrequency (%)
8.81
 
0.9%
7.81
 
0.9%
7.22
 
1.8%
6.66
5.3%
6.26
5.3%
3.61
 
0.9%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct46
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.68141593
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:21.792037image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q117
median27
Q351
95-th percentile93
Maximum100
Range99
Interquartile range (IQR)34

Descriptive statistics

Standard deviation28.23854556
Coefficient of variation (CV)0.7698324844
Kurtosis-0.5307522215
Mean36.68141593
Median Absolute Deviation (MAD)14
Skewness0.8000220076
Sum4145
Variance797.4154551
MonotonicityNot monotonic
2022-09-05T21:51:21.910497image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
518
 
7.1%
18
 
7.1%
347
 
6.2%
837
 
6.2%
217
 
6.2%
936
 
5.3%
274
 
3.5%
84
 
3.5%
133
 
2.7%
193
 
2.7%
Other values (36)56
49.6%
ValueCountFrequency (%)
18
7.1%
33
 
2.7%
51
 
0.9%
72
 
1.8%
84
3.5%
133
 
2.7%
142
 
1.8%
152
 
1.8%
163
 
2.7%
171
 
0.9%
ValueCountFrequency (%)
1001
 
0.9%
936
5.3%
921
 
0.9%
862
 
1.8%
837
6.2%
821
 
0.9%
811
 
0.9%
791
 
0.9%
781
 
0.9%
661
 
0.9%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct29
Distinct (%)25.9%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean88.74107143
Minimum1
Maximum447
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:22.009717image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.5
median30
Q3104
95-th percentile379
Maximum447
Range446
Interquartile range (IQR)101.5

Descriptive statistics

Standard deviation116.4046798
Coefficient of variation (CV)1.311733991
Kurtosis2.160789278
Mean88.74107143
Median Absolute Deviation (MAD)29
Skewness1.725766534
Sum9939
Variance13550.04947
MonotonicityNot monotonic
2022-09-05T21:51:22.112430image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
128
24.8%
2122
19.5%
10419
16.8%
676
 
5.3%
304
 
3.5%
3793
 
2.7%
1183
 
2.7%
512
 
1.8%
4472
 
1.8%
2262
 
1.8%
Other values (19)21
18.6%
ValueCountFrequency (%)
128
24.8%
31
 
0.9%
151
 
0.9%
201
 
0.9%
2122
19.5%
261
 
0.9%
304
 
3.5%
401
 
0.9%
451
 
0.9%
512
 
1.8%
ValueCountFrequency (%)
4472
1.8%
4451
 
0.9%
3802
1.8%
3793
2.7%
3661
 
0.9%
3271
 
0.9%
3111
 
0.9%
2451
 
0.9%
2381
 
0.9%
2262
1.8%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION

Distinct29
Distinct (%)25.9%
Missing1
Missing (%)0.9%
Memory size1.0 KiB
Netflix
28 
YouTube
22 
Tencent QQ
19 
iQIYI
Naver TVCast
Other values (24)
33 

Length

Max length17
Median length14
Mean length7.732142857
Min length4

Characters and Unicode

Total characters866
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)15.2%

Sample

1st rowYouTube
2nd rowOkko
3rd rowStart
4th rowTencent QQ
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
Netflix28
24.8%
YouTube22
19.5%
Tencent QQ19
16.8%
iQIYI6
 
5.3%
Naver TVCast4
 
3.5%
Shahid3
 
2.7%
Youku3
 
2.7%
Bilibili2
 
1.8%
GAIN2
 
1.8%
Mango TV2
 
1.8%
Other values (19)21
18.6%

Length

2022-09-05T21:51:22.213103image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
netflix28
18.5%
youtube22
14.6%
tencent19
12.6%
qq19
12.6%
tv7
 
4.6%
iqiyi6
 
4.0%
naver4
 
2.6%
tvcast4
 
2.6%
shahid3
 
2.0%
youku3
 
2.0%
Other values (31)36
23.8%

Most occurring characters

ValueCountFrequency (%)
e104
 
12.0%
t58
 
6.7%
T53
 
6.1%
u53
 
6.1%
i52
 
6.0%
Q44
 
5.1%
n44
 
5.1%
l39
 
4.5%
39
 
4.5%
N38
 
4.4%
Other values (39)342
39.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter573
66.2%
Uppercase Letter252
29.1%
Space Separator39
 
4.5%
Math Symbol1
 
0.1%
Decimal Number1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e104
18.2%
t58
10.1%
u53
9.2%
i52
9.1%
n44
7.7%
l39
 
6.8%
o37
 
6.5%
x28
 
4.9%
f28
 
4.9%
b25
 
4.4%
Other values (14)105
18.3%
Uppercase Letter
ValueCountFrequency (%)
T53
21.0%
Q44
17.5%
N38
15.1%
Y31
12.3%
I17
 
6.7%
V13
 
5.2%
C8
 
3.2%
S6
 
2.4%
B6
 
2.4%
P6
 
2.4%
Other values (12)30
11.9%
Space Separator
ValueCountFrequency (%)
39
100.0%
Math Symbol
ValueCountFrequency (%)
+1
100.0%
Decimal Number
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin825
95.3%
Common41
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e104
 
12.6%
t58
 
7.0%
T53
 
6.4%
u53
 
6.4%
i52
 
6.3%
Q44
 
5.3%
n44
 
5.3%
l39
 
4.7%
N38
 
4.6%
o37
 
4.5%
Other values (36)303
36.7%
Common
ValueCountFrequency (%)
39
95.1%
+1
 
2.4%
21
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII866
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e104
 
12.0%
t58
 
6.7%
T53
 
6.1%
u53
 
6.1%
i52
 
6.0%
Q44
 
5.1%
n44
 
5.1%
l39
 
4.5%
39
 
4.5%
N38
 
4.4%
Other values (39)342
39.5%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)13.5%
Missing24
Missing (%)21.2%
Memory size1.0 KiB
https://www.netflix.com/
28 
https://www.youtube.com
22 
https://v.qq.com/
19 
https://www.iq.com/
https://tv.naver.com/
Other values (7)
10 

Length

Max length30
Median length29
Mean length21.84269663
Min length17

Characters and Unicode

Total characters1944
Distinct characters28
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)4.5%

Sample

1st rowhttps://www.youtube.com
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://www.seezntv.com/
5th rowhttps://tv.naver.com/

Common Values

ValueCountFrequency (%)
https://www.netflix.com/28
24.8%
https://www.youtube.com22
19.5%
https://v.qq.com/19
16.8%
https://www.iq.com/6
 
5.3%
https://tv.naver.com/4
 
3.5%
https://www.seezntv.com/2
 
1.8%
https://w.mgtv.com/2
 
1.8%
https://www.linetv.tw/2
 
1.8%
https://www.primevideo.com1
 
0.9%
http://www.wowpresentsplus.com1
 
0.9%
Other values (2)2
 
1.8%
(Missing)24
21.2%

Length

2022-09-05T21:51:22.311703image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com28
31.5%
https://www.youtube.com22
24.7%
https://v.qq.com19
21.3%
https://www.iq.com6
 
6.7%
https://tv.naver.com4
 
4.5%
https://www.seezntv.com2
 
2.2%
https://w.mgtv.com2
 
2.2%
https://www.linetv.tw2
 
2.2%
https://www.primevideo.com1
 
1.1%
http://www.wowpresentsplus.com1
 
1.1%
Other values (2)2
 
2.2%

Most occurring characters

ValueCountFrequency (%)
/243
12.5%
t241
12.4%
w198
 
10.2%
.179
 
9.2%
o112
 
5.8%
s95
 
4.9%
p94
 
4.8%
h89
 
4.6%
m89
 
4.6%
c89
 
4.6%
Other values (18)515
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1433
73.7%
Other Punctuation511
 
26.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t241
16.8%
w198
13.8%
o112
 
7.8%
s95
 
6.6%
p94
 
6.6%
h89
 
6.2%
m89
 
6.2%
c89
 
6.2%
e66
 
4.6%
u47
 
3.3%
Other values (15)313
21.8%
Other Punctuation
ValueCountFrequency (%)
/243
47.6%
.179
35.0%
:89
 
17.4%

Most occurring scripts

ValueCountFrequency (%)
Latin1433
73.7%
Common511
 
26.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t241
16.8%
w198
13.8%
o112
 
7.8%
s95
 
6.6%
p94
 
6.6%
h89
 
6.2%
m89
 
6.2%
c89
 
6.2%
e66
 
4.6%
u47
 
3.3%
Other values (15)313
21.8%
Common
ValueCountFrequency (%)
/243
47.6%
.179
35.0%
:89
 
17.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/243
12.5%
t241
12.4%
w198
 
10.2%
.179
 
9.2%
o112
 
5.8%
s95
 
4.9%
p94
 
4.8%
h89
 
4.6%
m89
 
4.6%
c89
 
4.6%
Other values (18)515
26.5%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.externals.tvrage
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing110
Missing (%)97.3%
Memory size1.0 KiB
41967.0
19056.0
25100.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters21
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row41967.0
2nd row19056.0
3rd row25100.0

Common Values

ValueCountFrequency (%)
41967.01
 
0.9%
19056.01
 
0.9%
25100.01
 
0.9%
(Missing)110
97.3%

Length

2022-09-05T21:51:22.398859image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:22.483555image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
41967.01
33.3%
19056.01
33.3%
25100.01
33.3%

Most occurring characters

ValueCountFrequency (%)
06
28.6%
13
14.3%
.3
14.3%
92
 
9.5%
62
 
9.5%
52
 
9.5%
41
 
4.8%
71
 
4.8%
21
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18
85.7%
Other Punctuation3
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
06
33.3%
13
16.7%
92
 
11.1%
62
 
11.1%
52
 
11.1%
41
 
5.6%
71
 
5.6%
21
 
5.6%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
06
28.6%
13
14.3%
.3
14.3%
92
 
9.5%
62
 
9.5%
52
 
9.5%
41
 
4.8%
71
 
4.8%
21
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
06
28.6%
13
14.3%
.3
14.3%
92
 
9.5%
62
 
9.5%
52
 
9.5%
41
 
4.8%
71
 
4.8%
21
 
4.8%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct50
Distinct (%)61.0%
Missing31
Missing (%)27.4%
Infinite0
Infinite (%)0.0%
Mean369502.4634
Minimum104271
Maximum408034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:22.579072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile274405.9
Q1374690
median391910.5
Q3393381
95-th percentile395119.1
Maximum408034
Range303763
Interquartile range (IQR)18691

Descriptive statistics

Standard deviation51468.39951
Coefficient of variation (CV)0.1392910863
Kurtosis12.33747818
Mean369502.4634
Median Absolute Deviation (MAD)4087.5
Skewness-3.301920758
Sum30299202
Variance2648996148
MonotonicityNot monotonic
2022-09-05T21:51:22.698407image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3926578
 
7.1%
3776946
 
5.3%
3831526
 
5.3%
3942785
 
4.4%
3922143
 
2.7%
3602222
 
1.8%
3933812
 
1.8%
3924102
 
1.8%
3922272
 
1.8%
3926792
 
1.8%
Other values (40)44
38.9%
(Missing)31
27.4%
ValueCountFrequency (%)
1042711
0.9%
1445411
0.9%
2479561
0.9%
2651931
0.9%
2741751
0.9%
2787932
1.8%
2806191
0.9%
3150611
0.9%
3366281
0.9%
3386311
0.9%
ValueCountFrequency (%)
4080341
 
0.9%
4047691
 
0.9%
3961211
 
0.9%
3952351
 
0.9%
3951451
 
0.9%
3946271
 
0.9%
3942785
4.4%
3942252
 
1.8%
3942061
 
0.9%
3940871
 
0.9%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct32
Distinct (%)52.5%
Missing52
Missing (%)46.0%
Memory size1.0 KiB
tt13563634
tt9789660
tt10973800
tt13731400
tt13599000
 
2
Other values (27)
34 

Length

Max length10
Median length10
Mean length9.704918033
Min length9

Characters and Unicode

Total characters592
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)32.8%

Sample

1st rowtt13695606
2nd rowtt13423446
3rd rowtt11939550
4th rowtt11939550
5th rowtt13470370

Common Values

ValueCountFrequency (%)
tt135636348
 
7.1%
tt97896606
 
5.3%
tt109738006
 
5.3%
tt137314005
 
4.4%
tt135990002
 
1.8%
tt135688762
 
1.8%
tt114348742
 
1.8%
tt135989882
 
1.8%
tt134709842
 
1.8%
tt134703702
 
1.8%
Other values (22)24
21.2%
(Missing)52
46.0%

Length

2022-09-05T21:51:22.797204image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt135636348
 
13.1%
tt109738006
 
9.8%
tt97896606
 
9.8%
tt137314005
 
8.2%
tt134709842
 
3.3%
tt17148102
 
3.3%
tt134703702
 
3.3%
tt119395502
 
3.3%
tt135989882
 
3.3%
tt114348742
 
3.3%
Other values (22)24
39.3%

Most occurring characters

ValueCountFrequency (%)
t122
20.6%
170
11.8%
367
11.3%
064
10.8%
656
9.5%
948
 
8.1%
446
 
7.8%
839
 
6.6%
735
 
5.9%
532
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number470
79.4%
Lowercase Letter122
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
170
14.9%
367
14.3%
064
13.6%
656
11.9%
948
10.2%
446
9.8%
839
8.3%
735
7.4%
532
6.8%
213
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
t122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common470
79.4%
Latin122
 
20.6%

Most frequent character per script

Common
ValueCountFrequency (%)
170
14.9%
367
14.3%
064
13.6%
656
11.9%
948
10.2%
446
9.8%
839
8.3%
735
7.4%
532
6.8%
213
 
2.8%
Latin
ValueCountFrequency (%)
t122
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t122
20.6%
170
11.8%
367
11.3%
064
10.8%
656
9.5%
948
 
8.1%
446
 
7.8%
839
 
6.6%
735
 
5.9%
532
 
5.4%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)62.4%
Missing4
Missing (%)3.5%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/290/726567.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/284/712082.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/289/724883.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/405/1014510.jpg
 
6
https://static.tvmaze.com/uploads/images/medium_portrait/291/727946.jpg
 
5
Other values (63)
78 

Length

Max length72
Median length71
Mean length71.11009174
Min length70

Characters and Unicode

Total characters7751
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)45.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/282/706515.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/394/986714.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/267/669816.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/726567.jpg8
 
7.1%
https://static.tvmaze.com/uploads/images/medium_portrait/284/712082.jpg6
 
5.3%
https://static.tvmaze.com/uploads/images/medium_portrait/289/724883.jpg6
 
5.3%
https://static.tvmaze.com/uploads/images/medium_portrait/405/1014510.jpg6
 
5.3%
https://static.tvmaze.com/uploads/images/medium_portrait/291/727946.jpg5
 
4.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/medium_portrait/292/731904.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/281/703743.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/289/723488.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
1.8%
Other values (58)67
59.3%
(Missing)4
 
3.5%

Length

2022-09-05T21:51:22.886796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/290/726567.jpg8
 
7.3%
https://static.tvmaze.com/uploads/images/medium_portrait/289/724883.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/medium_portrait/405/1014510.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/medium_portrait/284/712082.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/medium_portrait/291/727946.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg3
 
2.8%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729467.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/189/473411.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/medium_portrait/370/926884.jpg2
 
1.8%
Other values (58)67
61.5%

Most occurring characters

ValueCountFrequency (%)
t763
 
9.8%
/763
 
9.8%
m545
 
7.0%
a545
 
7.0%
p436
 
5.6%
s436
 
5.6%
i436
 
5.6%
.327
 
4.2%
o327
 
4.2%
e327
 
4.2%
Other values (22)2846
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5450
70.3%
Other Punctuation1199
 
15.5%
Decimal Number993
 
12.8%
Connector Punctuation109
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t763
14.0%
m545
10.0%
a545
10.0%
p436
 
8.0%
s436
 
8.0%
i436
 
8.0%
o327
 
6.0%
e327
 
6.0%
u218
 
4.0%
d218
 
4.0%
Other values (8)1199
22.0%
Decimal Number
ValueCountFrequency (%)
2156
15.7%
7119
12.0%
1113
11.4%
8106
10.7%
9100
10.1%
498
9.9%
087
8.8%
377
7.8%
673
7.4%
564
6.4%
Other Punctuation
ValueCountFrequency (%)
/763
63.6%
.327
27.3%
:109
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5450
70.3%
Common2301
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t763
14.0%
m545
10.0%
a545
10.0%
p436
 
8.0%
s436
 
8.0%
i436
 
8.0%
o327
 
6.0%
e327
 
6.0%
u218
 
4.0%
d218
 
4.0%
Other values (8)1199
22.0%
Common
ValueCountFrequency (%)
/763
33.2%
.327
14.2%
2156
 
6.8%
7119
 
5.2%
1113
 
4.9%
_109
 
4.7%
:109
 
4.7%
8106
 
4.6%
9100
 
4.3%
498
 
4.3%
Other values (4)301
 
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII7751
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t763
 
9.8%
/763
 
9.8%
m545
 
7.0%
a545
 
7.0%
p436
 
5.6%
s436
 
5.6%
i436
 
5.6%
.327
 
4.2%
o327
 
4.2%
e327
 
4.2%
Other values (22)2846
36.7%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct68
Distinct (%)62.4%
Missing4
Missing (%)3.5%
Memory size1.0 KiB
https://static.tvmaze.com/uploads/images/original_untouched/290/726567.jpg
https://static.tvmaze.com/uploads/images/original_untouched/284/712082.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/289/724883.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/405/1014510.jpg
 
6
https://static.tvmaze.com/uploads/images/original_untouched/291/727946.jpg
 
5
Other values (63)
78 

Length

Max length75
Median length74
Mean length74.11009174
Min length73

Characters and Unicode

Total characters8078
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)45.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/315/789854.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/282/706515.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/394/986714.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/267/669816.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726567.jpg8
 
7.1%
https://static.tvmaze.com/uploads/images/original_untouched/284/712082.jpg6
 
5.3%
https://static.tvmaze.com/uploads/images/original_untouched/289/724883.jpg6
 
5.3%
https://static.tvmaze.com/uploads/images/original_untouched/405/1014510.jpg6
 
5.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/727946.jpg5
 
4.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg3
 
2.7%
https://static.tvmaze.com/uploads/images/original_untouched/292/731904.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/281/703743.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/289/723488.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
1.8%
Other values (58)67
59.3%
(Missing)4
 
3.5%

Length

2022-09-05T21:51:22.979143image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726567.jpg8
 
7.3%
https://static.tvmaze.com/uploads/images/original_untouched/289/724883.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/original_untouched/405/1014510.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/original_untouched/284/712082.jpg6
 
5.5%
https://static.tvmaze.com/uploads/images/original_untouched/291/727946.jpg5
 
4.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg3
 
2.8%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/291/729467.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/189/473411.jpg2
 
1.8%
https://static.tvmaze.com/uploads/images/original_untouched/370/926884.jpg2
 
1.8%
Other values (58)67
61.5%

Most occurring characters

ValueCountFrequency (%)
/763
 
9.4%
t654
 
8.1%
a545
 
6.7%
s436
 
5.4%
i436
 
5.4%
o436
 
5.4%
p327
 
4.0%
c327
 
4.0%
.327
 
4.0%
g327
 
4.0%
Other values (23)3500
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5777
71.5%
Other Punctuation1199
 
14.8%
Decimal Number993
 
12.3%
Connector Punctuation109
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t654
 
11.3%
a545
 
9.4%
s436
 
7.5%
i436
 
7.5%
o436
 
7.5%
p327
 
5.7%
c327
 
5.7%
g327
 
5.7%
m327
 
5.7%
e327
 
5.7%
Other values (9)1635
28.3%
Decimal Number
ValueCountFrequency (%)
2156
15.7%
7119
12.0%
1113
11.4%
8106
10.7%
9100
10.1%
498
9.9%
087
8.8%
377
7.8%
673
7.4%
564
6.4%
Other Punctuation
ValueCountFrequency (%)
/763
63.6%
.327
27.3%
:109
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5777
71.5%
Common2301
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t654
 
11.3%
a545
 
9.4%
s436
 
7.5%
i436
 
7.5%
o436
 
7.5%
p327
 
5.7%
c327
 
5.7%
g327
 
5.7%
m327
 
5.7%
e327
 
5.7%
Other values (9)1635
28.3%
Common
ValueCountFrequency (%)
/763
33.2%
.327
14.2%
2156
 
6.8%
7119
 
5.2%
1113
 
4.9%
:109
 
4.7%
_109
 
4.7%
8106
 
4.6%
9100
 
4.3%
498
 
4.3%
Other values (4)301
 
13.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII8078
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/763
 
9.4%
t654
 
8.1%
a545
 
6.7%
s436
 
5.4%
i436
 
5.4%
o436
 
5.4%
p327
 
4.0%
c327
 
4.0%
.327
 
4.0%
g327
 
4.0%
Other values (23)3500
43.3%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)60.6%
Missing9
Missing (%)8.0%
Memory size1.0 KiB
<p>The kings &amp; queens of leftover cooking will take a leftover dish on an epic journey across two rounds. Each half-hour after party, our home cooks will compete in the ultimate food makeover, finding ways to give old leftovers new life, all in the hopes of winning a $10,000 prize! Join host Jackie Tohn and judges David So and Rosemary Shrager as they watch our contestants transform leftovers into delicious creations. </p>
<p><b>Equinox</b> is a character-driven supernatural thriller about a young woman named Astrid, who is affected by the unexplainable disappearance of a school class in 1999. The series is set in Denmark and swipes back and forth between 1999, where it all started, and the present time.</p><p>Astrid is only 10 years old in the year 1999 when a class of graduating students inexplicably disappears without a trace. Astrid, who was close to one of the missing students becomes traumatized and plagued by horrific visions after the disappearance. In 2020, Astrid is peacefully living with her family when all of a sudden the nightmares come back and start haunting her. When the one survivor from 1999 mysteriously dies, Astrid is determined to find out what happened to the class, only to discover a dark and unsettling truth that involves her in ways she never imagined.</p>
 
6
<p><b>Transformers: War for Cybertron Trilogy</b> is a three-part arc following the war between the Autobots and Decepticons, complete with a new animation look and style.</p>
 
6
<p>Young noble Chu Yun Xiao crosses paths with female doctor Leng Xing Chen because of a beauty portrait. Together with their friends, the six people who are pulled into a terrifying conspiracy form a detective team to uncover the secrets surrounding the portrait. Chu Yunxiao has ventured into the pugilistic world for the first time. Aspiring to be a chivalrous hero, he relies on his outstanding martial arts skills and high intelligence to solve a difficult case. However, he unexpectedly discovers that he is also a chess piece in this dangerous game. As the fog is slowly lifted, Chu Yun Xiao becomes aware of an unbearable truth that the past twenty years of his life was nothing but a lie.</p>
 
6
<p>Amidst a heroin crisis, Vincenzo Muccioli cared for the addicted, earning him fierce public devotion — even as charges of violence began to mount.</p>
 
5
Other values (58)
73 

Length

Max length1253
Median length575
Mean length410.2980769
Min length58

Characters and Unicode

Total characters42671
Distinct characters89
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)42.3%

Sample

1st row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>
2nd row<p>One will to create oceans. One will to summon the mulberry fields.<br /><br />One will to slaughter countless devils. One will to eradicate innumerable immortals.<br /><br />Only my will… is eternal.<br /><br />A Will Eternal tells the tale of Bai Xiaochun, an endearing but exasperating young man who is driven primarily by his fear of death and desire to live forever, but who deeply values friendship and family.<br /><br />(Source: Novel Updates)</p>
3rd row<p>Da Eun works part-time and Kim Byul is an idol in her 5th years since debut. These two girls who look alike decide to change each other's lives just for 7 days. It tells the romantic encounters of these 2 girls.</p>
4th row<p>A teen romance of So Dam, a sixteen-year-old girl, who has never dated before but she receives her first-ever love confession from a mysterious boy. She is looking for the boy who secretly confessed to her while she was asleep on her desk. The clues include a male voice, mango fruit scent and gym uniform. She must piece the puzzle to find that person among the likely candidates that include hot shots Park Ji Hoo, Jeong Han Kyul, and Joo In Hyuk.</p>
5th row<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>

Common Values

ValueCountFrequency (%)
<p>The kings &amp; queens of leftover cooking will take a leftover dish on an epic journey across two rounds. Each half-hour after party, our home cooks will compete in the ultimate food makeover, finding ways to give old leftovers new life, all in the hopes of winning a $10,000 prize! Join host Jackie Tohn and judges David So and Rosemary Shrager as they watch our contestants transform leftovers into delicious creations. </p>8
 
7.1%
<p><b>Equinox</b> is a character-driven supernatural thriller about a young woman named Astrid, who is affected by the unexplainable disappearance of a school class in 1999. The series is set in Denmark and swipes back and forth between 1999, where it all started, and the present time.</p><p>Astrid is only 10 years old in the year 1999 when a class of graduating students inexplicably disappears without a trace. Astrid, who was close to one of the missing students becomes traumatized and plagued by horrific visions after the disappearance. In 2020, Astrid is peacefully living with her family when all of a sudden the nightmares come back and start haunting her. When the one survivor from 1999 mysteriously dies, Astrid is determined to find out what happened to the class, only to discover a dark and unsettling truth that involves her in ways she never imagined.</p>6
 
5.3%
<p><b>Transformers: War for Cybertron Trilogy</b> is a three-part arc following the war between the Autobots and Decepticons, complete with a new animation look and style.</p>6
 
5.3%
<p>Young noble Chu Yun Xiao crosses paths with female doctor Leng Xing Chen because of a beauty portrait. Together with their friends, the six people who are pulled into a terrifying conspiracy form a detective team to uncover the secrets surrounding the portrait. Chu Yunxiao has ventured into the pugilistic world for the first time. Aspiring to be a chivalrous hero, he relies on his outstanding martial arts skills and high intelligence to solve a difficult case. However, he unexpectedly discovers that he is also a chess piece in this dangerous game. As the fog is slowly lifted, Chu Yun Xiao becomes aware of an unbearable truth that the past twenty years of his life was nothing but a lie.</p>6
 
5.3%
<p>Amidst a heroin crisis, Vincenzo Muccioli cared for the addicted, earning him fierce public devotion — even as charges of violence began to mount.</p>5
 
4.4%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>3
 
2.7%
<p>‎At the end of the 20th century, due to the sudden decision of Xin Shensheng, gao Shan's business went bankrupt. Gao Shan wants to prove his father's innocence, but on his way suddenly falls in love with the daughter of Xin Shensheng, Tsin Waugh. Learning about the intentions of Gao Shan, Xin Shansheng makes him quit his job. ‎<br /><br />‎Gao Shan decides to go to Hong Kong to start from scratch, where he meets a benefactor and earns his first million in his life. Under the guidance of a mentor, he goes to Beijing and becomes a well-known investor. Soon Gao Shan meets Tsin Vo, who became a financial headhunter. Can love help them find their way to each other again? ‎<br /><br />‎Based on the novel by Xiao Moli "Little Storm 1.0"‎</p>2
 
1.8%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>2
 
1.8%
<p>Princess Ming Yue and Li Qiang, the emperor's ninth prince, are forced to marry in order to keep the peace in their kingdoms. As the princess finally seems to be getting used to her new life in Chang'An (an ancient Chinese capital), there are plots hovering against her and the royal family.</p>2
 
1.8%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>2
 
1.8%
Other values (53)62
54.9%
(Missing)9
 
8.0%

Length

2022-09-05T21:51:23.098810image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the371
 
5.2%
a255
 
3.6%
and227
 
3.2%
to201
 
2.8%
of179
 
2.5%
in132
 
1.9%
is92
 
1.3%
with75
 
1.1%
his65
 
0.9%
her65
 
0.9%
Other values (1646)5444
76.6%

Most occurring characters

ValueCountFrequency (%)
6985
16.4%
e3987
 
9.3%
t2674
 
6.3%
a2641
 
6.2%
n2467
 
5.8%
o2403
 
5.6%
i2398
 
5.6%
s2186
 
5.1%
r2086
 
4.9%
h1664
 
3.9%
Other values (79)13180
30.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter32439
76.0%
Space Separator7007
 
16.4%
Uppercase Letter1179
 
2.8%
Other Punctuation1014
 
2.4%
Math Symbol672
 
1.6%
Decimal Number244
 
0.6%
Dash Punctuation84
 
0.2%
Format12
 
< 0.1%
Currency Symbol8
 
< 0.1%
Open Punctuation6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3987
12.3%
t2674
 
8.2%
a2641
 
8.1%
n2467
 
7.6%
o2403
 
7.4%
i2398
 
7.4%
s2186
 
6.7%
r2086
 
6.4%
h1664
 
5.1%
l1271
 
3.9%
Other values (22)8662
26.7%
Uppercase Letter
ValueCountFrequency (%)
S120
 
10.2%
A111
 
9.4%
T99
 
8.4%
W83
 
7.0%
Y75
 
6.4%
C71
 
6.0%
L66
 
5.6%
D59
 
5.0%
M56
 
4.7%
X47
 
4.0%
Other values (16)392
33.2%
Other Punctuation
ValueCountFrequency (%)
,369
36.4%
.339
33.4%
/178
17.6%
'52
 
5.1%
"21
 
2.1%
!15
 
1.5%
:14
 
1.4%
?9
 
0.9%
;8
 
0.8%
&8
 
0.8%
Decimal Number
ValueCountFrequency (%)
976
31.1%
072
29.5%
151
20.9%
230
 
12.3%
85
 
2.0%
34
 
1.6%
53
 
1.2%
72
 
0.8%
41
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
-66
78.6%
16
 
19.0%
2
 
2.4%
Space Separator
ValueCountFrequency (%)
6985
99.7%
 22
 
0.3%
Math Symbol
ValueCountFrequency (%)
<336
50.0%
>336
50.0%
Format
ValueCountFrequency (%)
12
100.0%
Currency Symbol
ValueCountFrequency (%)
$8
100.0%
Open Punctuation
ValueCountFrequency (%)
(6
100.0%
Close Punctuation
ValueCountFrequency (%)
)6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin33618
78.8%
Common9053
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3987
11.9%
t2674
 
8.0%
a2641
 
7.9%
n2467
 
7.3%
o2403
 
7.1%
i2398
 
7.1%
s2186
 
6.5%
r2086
 
6.2%
h1664
 
4.9%
l1271
 
3.8%
Other values (48)9841
29.3%
Common
ValueCountFrequency (%)
6985
77.2%
,369
 
4.1%
.339
 
3.7%
<336
 
3.7%
>336
 
3.7%
/178
 
2.0%
976
 
0.8%
072
 
0.8%
-66
 
0.7%
'52
 
0.6%
Other values (21)244
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII42610
99.9%
Punctuation31
 
0.1%
None30
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6985
16.4%
e3987
 
9.4%
t2674
 
6.3%
a2641
 
6.2%
n2467
 
5.8%
o2403
 
5.6%
i2398
 
5.6%
s2186
 
5.1%
r2086
 
4.9%
h1664
 
3.9%
Other values (68)13119
30.8%
None
ValueCountFrequency (%)
 22
73.3%
á2
 
6.7%
č2
 
6.7%
ė1
 
3.3%
ū1
 
3.3%
é1
 
3.3%
å1
 
3.3%
Punctuation
ValueCountFrequency (%)
16
51.6%
12
38.7%
2
 
6.5%
1
 
3.2%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1636759762
Minimum1609402718
Maximum1662380496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:23.230044image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1609402718
5-th percentile1609482172
Q11613754307
median1645056856
Q31650908800
95-th percentile1661963386
Maximum1662380496
Range52977778
Interquartile range (IQR)37154493

Descriptive statistics

Standard deviation19411405.42
Coefficient of variation (CV)0.01185965459
Kurtosis-1.601644779
Mean1636759762
Median Absolute Deviation (MAD)16428873
Skewness-0.2213085581
Sum1.849538531 × 1011
Variance3.768026602 × 1014
MonotonicityNot monotonic
2022-09-05T21:51:23.356200image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16132149098
 
7.1%
16094027186
 
5.3%
16506226516
 
5.3%
16461207346
 
5.3%
16137543075
 
4.4%
16095351413
 
2.7%
16481900582
 
1.8%
16150585542
 
1.8%
16124781452
 
1.8%
16453704342
 
1.8%
Other values (62)71
62.8%
ValueCountFrequency (%)
16094027186
5.3%
16095351413
2.7%
16111891791
 
0.9%
16123781171
 
0.9%
16124781452
 
1.8%
16124799201
 
0.9%
16128425832
 
1.8%
16129809601
 
0.9%
16130883481
 
0.9%
16131479231
 
0.9%
ValueCountFrequency (%)
16623804961
0.9%
16623462771
0.9%
16622756681
0.9%
16622179311
0.9%
16620501331
0.9%
16619691591
0.9%
16619595381
0.9%
16618725611
0.9%
16618640441
0.9%
16616900451
0.9%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/shows/52615
 
8
https://api.tvmaze.com/shows/43890
 
6
https://api.tvmaze.com/shows/61556
 
6
https://api.tvmaze.com/shows/42387
 
6
https://api.tvmaze.com/shows/52708
 
5
Other values (67)
82 

Length

Max length34
Median length34
Mean length33.96460177
Min length33

Characters and Unicode

Total characters3838
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.9%

Sample

1st rowhttps://api.tvmaze.com/shows/49630
2nd rowhttps://api.tvmaze.com/shows/51510
3rd rowhttps://api.tvmaze.com/shows/52499
4th rowhttps://api.tvmaze.com/shows/49206
5th rowhttps://api.tvmaze.com/shows/49652

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/526158
 
7.1%
https://api.tvmaze.com/shows/438906
 
5.3%
https://api.tvmaze.com/shows/615566
 
5.3%
https://api.tvmaze.com/shows/423876
 
5.3%
https://api.tvmaze.com/shows/527085
 
4.4%
https://api.tvmaze.com/shows/521043
 
2.7%
https://api.tvmaze.com/shows/152502
 
1.8%
https://api.tvmaze.com/shows/472262
 
1.8%
https://api.tvmaze.com/shows/525242
 
1.8%
https://api.tvmaze.com/shows/529312
 
1.8%
Other values (62)71
62.8%

Length

2022-09-05T21:51:23.461130image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/526158
 
7.1%
https://api.tvmaze.com/shows/615566
 
5.3%
https://api.tvmaze.com/shows/423876
 
5.3%
https://api.tvmaze.com/shows/438906
 
5.3%
https://api.tvmaze.com/shows/527085
 
4.4%
https://api.tvmaze.com/shows/521043
 
2.7%
https://api.tvmaze.com/shows/586892
 
1.8%
https://api.tvmaze.com/shows/527432
 
1.8%
https://api.tvmaze.com/shows/524212
 
1.8%
https://api.tvmaze.com/shows/524002
 
1.8%
Other values (62)71
62.8%

Most occurring characters

ValueCountFrequency (%)
/452
 
11.8%
s339
 
8.8%
t339
 
8.8%
h226
 
5.9%
p226
 
5.9%
a226
 
5.9%
o226
 
5.9%
.226
 
5.9%
m226
 
5.9%
e113
 
2.9%
Other values (16)1239
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2486
64.8%
Other Punctuation791
 
20.6%
Decimal Number561
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s339
13.6%
t339
13.6%
h226
9.1%
p226
9.1%
a226
9.1%
o226
9.1%
m226
9.1%
e113
 
4.5%
w113
 
4.5%
c113
 
4.5%
Other values (3)339
13.6%
Decimal Number
ValueCountFrequency (%)
5104
18.5%
274
13.2%
469
12.3%
659
10.5%
148
8.6%
846
8.2%
044
7.8%
742
7.5%
340
 
7.1%
935
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/452
57.1%
.226
28.6%
:113
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2486
64.8%
Common1352
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/452
33.4%
.226
16.7%
:113
 
8.4%
5104
 
7.7%
274
 
5.5%
469
 
5.1%
659
 
4.4%
148
 
3.6%
846
 
3.4%
044
 
3.3%
Other values (3)117
 
8.7%
Latin
ValueCountFrequency (%)
s339
13.6%
t339
13.6%
h226
9.1%
p226
9.1%
a226
9.1%
o226
9.1%
m226
9.1%
e113
 
4.5%
w113
 
4.5%
c113
 
4.5%
Other values (3)339
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/452
 
11.8%
s339
 
8.8%
t339
 
8.8%
h226
 
5.9%
p226
 
5.9%
a226
 
5.9%
o226
 
5.9%
.226
 
5.9%
m226
 
5.9%
e113
 
2.9%
Other values (16)1239
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct72
Distinct (%)63.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/1995747
 
8
https://api.tvmaze.com/episodes/1976487
 
6
https://api.tvmaze.com/episodes/2312241
 
6
https://api.tvmaze.com/episodes/2137797
 
6
https://api.tvmaze.com/episodes/1995755
 
5
Other values (67)
82 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters4407
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)46.9%

Sample

1st rowhttps://api.tvmaze.com/episodes/2380515
2nd rowhttps://api.tvmaze.com/episodes/2287139
3rd rowhttps://api.tvmaze.com/episodes/2270905
4th rowhttps://api.tvmaze.com/episodes/2386129
5th rowhttps://api.tvmaze.com/episodes/2374448

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19957478
 
7.1%
https://api.tvmaze.com/episodes/19764876
 
5.3%
https://api.tvmaze.com/episodes/23122416
 
5.3%
https://api.tvmaze.com/episodes/21377976
 
5.3%
https://api.tvmaze.com/episodes/19957555
 
4.4%
https://api.tvmaze.com/episodes/19760543
 
2.7%
https://api.tvmaze.com/episodes/23012762
 
1.8%
https://api.tvmaze.com/episodes/20427182
 
1.8%
https://api.tvmaze.com/episodes/19880792
 
1.8%
https://api.tvmaze.com/episodes/22801692
 
1.8%
Other values (62)71
62.8%

Length

2022-09-05T21:51:23.554788image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19957478
 
7.1%
https://api.tvmaze.com/episodes/23122416
 
5.3%
https://api.tvmaze.com/episodes/21377976
 
5.3%
https://api.tvmaze.com/episodes/19764876
 
5.3%
https://api.tvmaze.com/episodes/19957555
 
4.4%
https://api.tvmaze.com/episodes/19760543
 
2.7%
https://api.tvmaze.com/episodes/22059832
 
1.8%
https://api.tvmaze.com/episodes/19975522
 
1.8%
https://api.tvmaze.com/episodes/19854962
 
1.8%
https://api.tvmaze.com/episodes/19849632
 
1.8%
Other values (62)71
62.8%

Most occurring characters

ValueCountFrequency (%)
/452
 
10.3%
t339
 
7.7%
p339
 
7.7%
s339
 
7.7%
e339
 
7.7%
a226
 
5.1%
i226
 
5.1%
.226
 
5.1%
m226
 
5.1%
o226
 
5.1%
Other values (16)1469
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2825
64.1%
Other Punctuation791
 
17.9%
Decimal Number791
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t339
12.0%
p339
12.0%
s339
12.0%
e339
12.0%
a226
8.0%
i226
8.0%
m226
8.0%
o226
8.0%
h113
 
4.0%
d113
 
4.0%
Other values (3)339
12.0%
Decimal Number
ValueCountFrequency (%)
2139
17.6%
999
12.5%
197
12.3%
797
12.3%
368
8.6%
467
8.5%
566
8.3%
065
8.2%
851
 
6.4%
642
 
5.3%
Other Punctuation
ValueCountFrequency (%)
/452
57.1%
.226
28.6%
:113
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2825
64.1%
Common1582
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/452
28.6%
.226
14.3%
2139
 
8.8%
:113
 
7.1%
999
 
6.3%
197
 
6.1%
797
 
6.1%
368
 
4.3%
467
 
4.2%
566
 
4.2%
Other values (3)158
 
10.0%
Latin
ValueCountFrequency (%)
t339
12.0%
p339
12.0%
s339
12.0%
e339
12.0%
a226
8.0%
i226
8.0%
m226
8.0%
o226
8.0%
h113
 
4.0%
d113
 
4.0%
Other values (3)339
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/452
 
10.3%
t339
 
7.7%
p339
 
7.7%
s339
 
7.7%
e339
 
7.7%
a226
 
5.1%
i226
 
5.1%
.226
 
5.1%
m226
 
5.1%
o226
 
5.1%
Other values (16)1469
33.3%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)17.4%
Missing67
Missing (%)59.3%
Memory size1.0 KiB
China
26 
Korea, Republic of
United States
Russian Federation
 
2
Taiwan, Province of China
 
2
Other values (3)

Length

Max length25
Median length5
Mean length9.282608696
Min length5

Characters and Unicode

Total characters427
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowChina
4th rowChina
5th rowKorea, Republic of

Common Values

ValueCountFrequency (%)
China26
 
23.0%
Korea, Republic of6
 
5.3%
United States5
 
4.4%
Russian Federation2
 
1.8%
Taiwan, Province of China2
 
1.8%
Turkey2
 
1.8%
Norway2
 
1.8%
United Kingdom1
 
0.9%
(Missing)67
59.3%

Length

2022-09-05T21:51:23.647656image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:23.753121image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china28
38.9%
of8
 
11.1%
korea6
 
8.3%
republic6
 
8.3%
united6
 
8.3%
states5
 
6.9%
russian2
 
2.8%
federation2
 
2.8%
taiwan2
 
2.8%
province2
 
2.8%
Other values (3)5
 
6.9%

Most occurring characters

ValueCountFrequency (%)
i49
11.5%
a49
11.5%
n43
 
10.1%
e31
 
7.3%
C28
 
6.6%
h28
 
6.6%
26
 
6.1%
o21
 
4.9%
t18
 
4.2%
r14
 
3.3%
Other values (23)120
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter329
77.0%
Uppercase Letter64
 
15.0%
Space Separator26
 
6.1%
Other Punctuation8
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i49
14.9%
a49
14.9%
n43
13.1%
e31
9.4%
h28
8.5%
o21
 
6.4%
t18
 
5.5%
r14
 
4.3%
u10
 
3.0%
s9
 
2.7%
Other values (12)57
17.3%
Uppercase Letter
ValueCountFrequency (%)
C28
43.8%
R8
 
12.5%
K7
 
10.9%
U6
 
9.4%
S5
 
7.8%
T4
 
6.2%
P2
 
3.1%
F2
 
3.1%
N2
 
3.1%
Space Separator
ValueCountFrequency (%)
26
100.0%
Other Punctuation
ValueCountFrequency (%)
,8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin393
92.0%
Common34
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i49
12.5%
a49
12.5%
n43
10.9%
e31
 
7.9%
C28
 
7.1%
h28
 
7.1%
o21
 
5.3%
t18
 
4.6%
r14
 
3.6%
u10
 
2.5%
Other values (21)102
26.0%
Common
ValueCountFrequency (%)
26
76.5%
,8
 
23.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII427
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i49
11.5%
a49
11.5%
n43
 
10.1%
e31
 
7.3%
C28
 
6.6%
h28
 
6.6%
26
 
6.1%
o21
 
4.9%
t18
 
4.2%
r14
 
3.3%
Other values (23)120
28.1%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)17.4%
Missing67
Missing (%)59.3%
Memory size1.0 KiB
CN
26 
KR
US
RU
 
2
TW
 
2
Other values (3)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters92
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st rowRU
2nd rowRU
3rd rowCN
4th rowCN
5th rowKR

Common Values

ValueCountFrequency (%)
CN26
 
23.0%
KR6
 
5.3%
US5
 
4.4%
RU2
 
1.8%
TW2
 
1.8%
TR2
 
1.8%
NO2
 
1.8%
GB1
 
0.9%
(Missing)67
59.3%

Length

2022-09-05T21:51:23.841481image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:23.932551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn26
56.5%
kr6
 
13.0%
us5
 
10.9%
ru2
 
4.3%
tw2
 
4.3%
tr2
 
4.3%
no2
 
4.3%
gb1
 
2.2%

Most occurring characters

ValueCountFrequency (%)
N28
30.4%
C26
28.3%
R10
 
10.9%
U7
 
7.6%
K6
 
6.5%
S5
 
5.4%
T4
 
4.3%
W2
 
2.2%
O2
 
2.2%
G1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter92
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N28
30.4%
C26
28.3%
R10
 
10.9%
U7
 
7.6%
K6
 
6.5%
S5
 
5.4%
T4
 
4.3%
W2
 
2.2%
O2
 
2.2%
G1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin92
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N28
30.4%
C26
28.3%
R10
 
10.9%
U7
 
7.6%
K6
 
6.5%
S5
 
5.4%
T4
 
4.3%
W2
 
2.2%
O2
 
2.2%
G1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N28
30.4%
C26
28.3%
R10
 
10.9%
U7
 
7.6%
K6
 
6.5%
S5
 
5.4%
T4
 
4.3%
W2
 
2.2%
O2
 
2.2%
G1
 
1.1%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)17.4%
Missing67
Missing (%)59.3%
Memory size1.0 KiB
Asia/Shanghai
26 
Asia/Seoul
America/New_York
Asia/Kamchatka
 
2
Asia/Taipei
 
2
Other values (3)

Length

Max length16
Median length13
Mean length12.89130435
Min length10

Characters and Unicode

Total characters593
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Shanghai
4th rowAsia/Shanghai
5th rowAsia/Seoul

Common Values

ValueCountFrequency (%)
Asia/Shanghai26
 
23.0%
Asia/Seoul6
 
5.3%
America/New_York5
 
4.4%
Asia/Kamchatka2
 
1.8%
Asia/Taipei2
 
1.8%
Europe/Istanbul2
 
1.8%
Europe/Oslo2
 
1.8%
Europe/London1
 
0.9%
(Missing)67
59.3%

Length

2022-09-05T21:51:24.024996image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:24.126490image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai26
56.5%
asia/seoul6
 
13.0%
america/new_york5
 
10.9%
asia/kamchatka2
 
4.3%
asia/taipei2
 
4.3%
europe/istanbul2
 
4.3%
europe/oslo2
 
4.3%
europe/london1
 
2.2%

Most occurring characters

ValueCountFrequency (%)
a103
17.4%
i71
12.0%
h54
9.1%
/46
 
7.8%
A41
 
6.9%
s40
 
6.7%
S32
 
5.4%
n30
 
5.1%
g26
 
4.4%
e23
 
3.9%
Other values (21)127
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter445
75.0%
Uppercase Letter97
 
16.4%
Other Punctuation46
 
7.8%
Connector Punctuation5
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a103
23.1%
i71
16.0%
h54
12.1%
s40
 
9.0%
n30
 
6.7%
g26
 
5.8%
e23
 
5.2%
o20
 
4.5%
r15
 
3.4%
u13
 
2.9%
Other values (9)50
11.2%
Uppercase Letter
ValueCountFrequency (%)
A41
42.3%
S32
33.0%
Y5
 
5.2%
N5
 
5.2%
E5
 
5.2%
K2
 
2.1%
T2
 
2.1%
I2
 
2.1%
O2
 
2.1%
L1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
/46
100.0%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin542
91.4%
Common51
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a103
19.0%
i71
13.1%
h54
10.0%
A41
 
7.6%
s40
 
7.4%
S32
 
5.9%
n30
 
5.5%
g26
 
4.8%
e23
 
4.2%
o20
 
3.7%
Other values (19)102
18.8%
Common
ValueCountFrequency (%)
/46
90.2%
_5
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII593
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a103
17.4%
i71
12.0%
h54
9.1%
/46
 
7.8%
A41
 
6.9%
s40
 
6.7%
S32
 
5.4%
n30
 
5.1%
g26
 
4.4%
e23
 
3.9%
Other values (21)127
21.4%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing108
Missing (%)95.6%
Memory size1.0 KiB
https://api.tvmaze.com/episodes/2374449
https://api.tvmaze.com/episodes/2383014
https://api.tvmaze.com/episodes/2330185
https://api.tvmaze.com/episodes/2379703
https://api.tvmaze.com/episodes/2367107

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2374449
2nd rowhttps://api.tvmaze.com/episodes/2383014
3rd rowhttps://api.tvmaze.com/episodes/2330185
4th rowhttps://api.tvmaze.com/episodes/2379703
5th rowhttps://api.tvmaze.com/episodes/2367107

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
 
0.9%
https://api.tvmaze.com/episodes/23830141
 
0.9%
https://api.tvmaze.com/episodes/23301851
 
0.9%
https://api.tvmaze.com/episodes/23797031
 
0.9%
https://api.tvmaze.com/episodes/23671071
 
0.9%
(Missing)108
95.6%

Length

2022-09-05T21:51:24.216291image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:24.305707image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23744491
20.0%
https://api.tvmaze.com/episodes/23830141
20.0%
https://api.tvmaze.com/episodes/23301851
20.0%
https://api.tvmaze.com/episodes/23797031
20.0%
https://api.tvmaze.com/episodes/23671071
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
38
22.9%
75
14.3%
25
14.3%
44
11.4%
04
11.4%
13
 
8.6%
92
 
5.7%
82
 
5.7%
51
 
2.9%
61
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/20
28.6%
.10
14.3%
38
 
11.4%
75
 
7.1%
25
 
7.1%
:5
 
7.1%
44
 
5.7%
04
 
5.7%
13
 
4.3%
92
 
2.9%
Other values (3)4
 
5.7%
Latin
ValueCountFrequency (%)
p15
12.0%
s15
12.0%
e15
12.0%
t15
12.0%
a10
8.0%
i10
8.0%
m10
8.0%
o10
8.0%
h5
 
4.0%
d5
 
4.0%
Other values (3)15
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
p15
 
7.7%
s15
 
7.7%
e15
 
7.7%
t15
 
7.7%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
m10
 
5.1%
o10
 
5.1%
Other values (16)65
33.3%

_embedded.show.dvdCountry.name
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing111
Missing (%)98.2%
Memory size1.0 KiB
Korea, Republic of
Ukraine

Length

Max length18
Median length12.5
Mean length12.5
Min length7

Characters and Unicode

Total characters25
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowKorea, Republic of
2nd rowUkraine

Common Values

ValueCountFrequency (%)
Korea, Republic of1
 
0.9%
Ukraine1
 
0.9%
(Missing)111
98.2%

Length

2022-09-05T21:51:24.394812image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:24.481889image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
korea1
25.0%
republic1
25.0%
of1
25.0%
ukraine1
25.0%

Most occurring characters

ValueCountFrequency (%)
e3
 
12.0%
i2
 
8.0%
r2
 
8.0%
a2
 
8.0%
2
 
8.0%
o2
 
8.0%
K1
 
4.0%
k1
 
4.0%
U1
 
4.0%
f1
 
4.0%
Other values (8)8
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19
76.0%
Uppercase Letter3
 
12.0%
Space Separator2
 
8.0%
Other Punctuation1
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3
15.8%
i2
10.5%
r2
10.5%
a2
10.5%
o2
10.5%
k1
 
5.3%
f1
 
5.3%
c1
 
5.3%
u1
 
5.3%
l1
 
5.3%
Other values (3)3
15.8%
Uppercase Letter
ValueCountFrequency (%)
K1
33.3%
U1
33.3%
R1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
,1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin22
88.0%
Common3
 
12.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3
13.6%
i2
 
9.1%
r2
 
9.1%
a2
 
9.1%
o2
 
9.1%
K1
 
4.5%
k1
 
4.5%
U1
 
4.5%
f1
 
4.5%
c1
 
4.5%
Other values (6)6
27.3%
Common
ValueCountFrequency (%)
2
66.7%
,1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e3
 
12.0%
i2
 
8.0%
r2
 
8.0%
a2
 
8.0%
2
 
8.0%
o2
 
8.0%
K1
 
4.0%
k1
 
4.0%
U1
 
4.0%
f1
 
4.0%
Other values (8)8
32.0%

_embedded.show.dvdCountry.code
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing111
Missing (%)98.2%
Memory size1.0 KiB
KR
UA

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowKR
2nd rowUA

Common Values

ValueCountFrequency (%)
KR1
 
0.9%
UA1
 
0.9%
(Missing)111
98.2%

Length

2022-09-05T21:51:24.565344image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:24.655561image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
kr1
50.0%
ua1
50.0%

Most occurring characters

ValueCountFrequency (%)
K1
25.0%
R1
25.0%
U1
25.0%
A1
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K1
25.0%
R1
25.0%
U1
25.0%
A1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K1
25.0%
R1
25.0%
U1
25.0%
A1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K1
25.0%
R1
25.0%
U1
25.0%
A1
25.0%

_embedded.show.dvdCountry.timezone
Categorical

MISSING
UNIFORM

Distinct2
Distinct (%)100.0%
Missing111
Missing (%)98.2%
Memory size1.0 KiB
Asia/Seoul
Europe/Zaporozhye

Length

Max length17
Median length13.5
Mean length13.5
Min length10

Characters and Unicode

Total characters27
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowAsia/Seoul
2nd rowEurope/Zaporozhye

Common Values

ValueCountFrequency (%)
Asia/Seoul1
 
0.9%
Europe/Zaporozhye1
 
0.9%
(Missing)111
98.2%

Length

2022-09-05T21:51:24.740168image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:24.832031image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/seoul1
50.0%
europe/zaporozhye1
50.0%

Most occurring characters

ValueCountFrequency (%)
o4
14.8%
e3
11.1%
u2
 
7.4%
r2
 
7.4%
a2
 
7.4%
/2
 
7.4%
p2
 
7.4%
h1
 
3.7%
z1
 
3.7%
Z1
 
3.7%
Other values (7)7
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter21
77.8%
Uppercase Letter4
 
14.8%
Other Punctuation2
 
7.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o4
19.0%
e3
14.3%
u2
9.5%
r2
9.5%
a2
9.5%
p2
9.5%
h1
 
4.8%
z1
 
4.8%
l1
 
4.8%
s1
 
4.8%
Other values (2)2
9.5%
Uppercase Letter
ValueCountFrequency (%)
Z1
25.0%
A1
25.0%
E1
25.0%
S1
25.0%
Other Punctuation
ValueCountFrequency (%)
/2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin25
92.6%
Common2
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o4
16.0%
e3
12.0%
u2
 
8.0%
r2
 
8.0%
a2
 
8.0%
p2
 
8.0%
h1
 
4.0%
z1
 
4.0%
Z1
 
4.0%
A1
 
4.0%
Other values (6)6
24.0%
Common
ValueCountFrequency (%)
/2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o4
14.8%
e3
11.1%
u2
 
7.4%
r2
 
7.4%
a2
 
7.4%
/2
 
7.4%
p2
 
7.4%
h1
 
3.7%
z1
 
3.7%
Z1
 
3.7%
Other values (7)7
25.9%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)100.0%
Missing107
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean448.1666667
Minimum30
Maximum1808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2022-09-05T21:51:24.896796image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50.5
Q1117
median168.5
Q3352.75
95-th percentile1456.5
Maximum1808
Range1778
Interquartile range (IQR)235.75

Descriptive statistics

Standard deviation677.9735737
Coefficient of variation (CV)1.512771083
Kurtosis5.267277135
Mean448.1666667
Median Absolute Deviation (MAD)97.5
Skewness2.269367844
Sum2689
Variance459648.1667
MonotonicityNot monotonic
2022-09-05T21:51:24.980338image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
18081
 
0.9%
2051
 
0.9%
4021
 
0.9%
1121
 
0.9%
301
 
0.9%
1321
 
0.9%
(Missing)107
94.7%
ValueCountFrequency (%)
301
0.9%
1121
0.9%
1321
0.9%
2051
0.9%
4021
0.9%
18081
0.9%
ValueCountFrequency (%)
18081
0.9%
4021
0.9%
2051
0.9%
1321
0.9%
1121
0.9%
301
0.9%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing107
Missing (%)94.7%
Memory size1.0 KiB
MBC Masr
NFL Network
Новий Канал
RTL4
USA Network

Length

Max length11
Median length9.5
Mean length8.833333333
Min length4

Characters and Unicode

Total characters53
Distinct characters32
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowMBC Masr
2nd rowNFL Network
3rd rowНовий Канал
4th rowRTL4
5th rowUSA Network

Common Values

ValueCountFrequency (%)
MBC Masr1
 
0.9%
NFL Network1
 
0.9%
Новий Канал1
 
0.9%
RTL41
 
0.9%
USA Network1
 
0.9%
Tokyo MX1
 
0.9%
(Missing)107
94.7%

Length

2022-09-05T21:51:25.075091image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:25.175357image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
network2
18.2%
mbc1
9.1%
masr1
9.1%
nfl1
9.1%
новий1
9.1%
канал1
9.1%
rtl41
9.1%
usa1
9.1%
tokyo1
9.1%
mx1
9.1%

Most occurring characters

ValueCountFrequency (%)
5
 
9.4%
o4
 
7.5%
M3
 
5.7%
k3
 
5.7%
r3
 
5.7%
N3
 
5.7%
а2
 
3.8%
T2
 
3.8%
w2
 
3.8%
t2
 
3.8%
Other values (22)24
45.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter27
50.9%
Uppercase Letter20
37.7%
Space Separator5
 
9.4%
Decimal Number1
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o4
14.8%
k3
11.1%
r3
11.1%
а2
 
7.4%
w2
 
7.4%
t2
 
7.4%
e2
 
7.4%
y1
 
3.7%
л1
 
3.7%
н1
 
3.7%
Other values (6)6
22.2%
Uppercase Letter
ValueCountFrequency (%)
M3
15.0%
N3
15.0%
T2
10.0%
L2
10.0%
U1
 
5.0%
S1
 
5.0%
A1
 
5.0%
R1
 
5.0%
К1
 
5.0%
B1
 
5.0%
Other values (4)4
20.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Decimal Number
ValueCountFrequency (%)
41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin37
69.8%
Cyrillic10
 
18.9%
Common6
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o4
 
10.8%
M3
 
8.1%
k3
 
8.1%
r3
 
8.1%
N3
 
8.1%
T2
 
5.4%
w2
 
5.4%
t2
 
5.4%
e2
 
5.4%
L2
 
5.4%
Other values (11)11
29.7%
Cyrillic
ValueCountFrequency (%)
а2
20.0%
л1
10.0%
н1
10.0%
о1
10.0%
К1
10.0%
й1
10.0%
и1
10.0%
в1
10.0%
Н1
10.0%
Common
ValueCountFrequency (%)
5
83.3%
41
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII43
81.1%
Cyrillic10
 
18.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
 
11.6%
o4
 
9.3%
M3
 
7.0%
k3
 
7.0%
r3
 
7.0%
N3
 
7.0%
T2
 
4.7%
w2
 
4.7%
t2
 
4.7%
e2
 
4.7%
Other values (13)14
32.6%
Cyrillic
ValueCountFrequency (%)
а2
20.0%
л1
10.0%
н1
10.0%
о1
10.0%
К1
10.0%
й1
10.0%
и1
10.0%
в1
10.0%
Н1
10.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing107
Missing (%)94.7%
Memory size1.0 KiB
United States
Egypt
Ukraine
Netherlands
Japan

Length

Max length13
Median length11
Mean length9
Min length5

Characters and Unicode

Total characters54
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st rowEgypt
2nd rowUnited States
3rd rowUkraine
4th rowNetherlands
5th rowUnited States

Common Values

ValueCountFrequency (%)
United States2
 
1.8%
Egypt1
 
0.9%
Ukraine1
 
0.9%
Netherlands1
 
0.9%
Japan1
 
0.9%
(Missing)107
94.7%

Length

2022-09-05T21:51:25.273513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:25.378564image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
united2
25.0%
states2
25.0%
egypt1
12.5%
ukraine1
12.5%
netherlands1
12.5%
japan1
12.5%

Most occurring characters

ValueCountFrequency (%)
t8
14.8%
e7
13.0%
a6
11.1%
n5
9.3%
U3
 
5.6%
i3
 
5.6%
d3
 
5.6%
s3
 
5.6%
r2
 
3.7%
2
 
3.7%
Other values (10)12
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter44
81.5%
Uppercase Letter8
 
14.8%
Space Separator2
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t8
18.2%
e7
15.9%
a6
13.6%
n5
11.4%
i3
 
6.8%
d3
 
6.8%
s3
 
6.8%
r2
 
4.5%
p2
 
4.5%
l1
 
2.3%
Other values (4)4
9.1%
Uppercase Letter
ValueCountFrequency (%)
U3
37.5%
S2
25.0%
N1
 
12.5%
E1
 
12.5%
J1
 
12.5%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin52
96.3%
Common2
 
3.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t8
15.4%
e7
13.5%
a6
11.5%
n5
9.6%
U3
 
5.8%
i3
 
5.8%
d3
 
5.8%
s3
 
5.8%
r2
 
3.8%
S2
 
3.8%
Other values (9)10
19.2%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t8
14.8%
e7
13.0%
a6
11.1%
n5
9.3%
U3
 
5.6%
i3
 
5.6%
d3
 
5.6%
s3
 
5.6%
r2
 
3.7%
2
 
3.7%
Other values (10)12
22.2%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing107
Missing (%)94.7%
Memory size1.0 KiB
US
EG
UA
NL
JP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters12
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st rowEG
2nd rowUS
3rd rowUA
4th rowNL
5th rowUS

Common Values

ValueCountFrequency (%)
US2
 
1.8%
EG1
 
0.9%
UA1
 
0.9%
NL1
 
0.9%
JP1
 
0.9%
(Missing)107
94.7%

Length

2022-09-05T21:51:25.467118image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:25.557980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
us2
33.3%
eg1
16.7%
ua1
16.7%
nl1
16.7%
jp1
16.7%

Most occurring characters

ValueCountFrequency (%)
U3
25.0%
S2
16.7%
E1
 
8.3%
G1
 
8.3%
A1
 
8.3%
N1
 
8.3%
L1
 
8.3%
J1
 
8.3%
P1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter12
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U3
25.0%
S2
16.7%
E1
 
8.3%
G1
 
8.3%
A1
 
8.3%
N1
 
8.3%
L1
 
8.3%
J1
 
8.3%
P1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Latin12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U3
25.0%
S2
16.7%
E1
 
8.3%
G1
 
8.3%
A1
 
8.3%
N1
 
8.3%
L1
 
8.3%
J1
 
8.3%
P1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U3
25.0%
S2
16.7%
E1
 
8.3%
G1
 
8.3%
A1
 
8.3%
N1
 
8.3%
L1
 
8.3%
J1
 
8.3%
P1
 
8.3%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)83.3%
Missing107
Missing (%)94.7%
Memory size1.0 KiB
America/New_York
Africa/Cairo
Europe/Zaporozhye
Europe/Amsterdam
Asia/Tokyo

Length

Max length17
Median length16.5
Mean length14.5
Min length10

Characters and Unicode

Total characters87
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st rowAfrica/Cairo
2nd rowAmerica/New_York
3rd rowEurope/Zaporozhye
4th rowEurope/Amsterdam
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
America/New_York2
 
1.8%
Africa/Cairo1
 
0.9%
Europe/Zaporozhye1
 
0.9%
Europe/Amsterdam1
 
0.9%
Asia/Tokyo1
 
0.9%
(Missing)107
94.7%

Length

2022-09-05T21:51:25.651165image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:51:25.749387image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
america/new_york2
33.3%
africa/cairo1
16.7%
europe/zaporozhye1
16.7%
europe/amsterdam1
16.7%
asia/tokyo1
16.7%

Most occurring characters

ValueCountFrequency (%)
r10
 
11.5%
o9
 
10.3%
e8
 
9.2%
a7
 
8.0%
/6
 
6.9%
A5
 
5.7%
i5
 
5.7%
m4
 
4.6%
p3
 
3.4%
k3
 
3.4%
Other values (17)27
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter65
74.7%
Uppercase Letter14
 
16.1%
Other Punctuation6
 
6.9%
Connector Punctuation2
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r10
15.4%
o9
13.8%
e8
12.3%
a7
10.8%
i5
7.7%
m4
 
6.2%
p3
 
4.6%
k3
 
4.6%
c3
 
4.6%
s2
 
3.1%
Other values (8)11
16.9%
Uppercase Letter
ValueCountFrequency (%)
A5
35.7%
E2
 
14.3%
Y2
 
14.3%
N2
 
14.3%
C1
 
7.1%
Z1
 
7.1%
T1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin79
90.8%
Common8
 
9.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r10
12.7%
o9
11.4%
e8
 
10.1%
a7
 
8.9%
A5
 
6.3%
i5
 
6.3%
m4
 
5.1%
p3
 
3.8%
k3
 
3.8%
c3
 
3.8%
Other values (15)22
27.8%
Common
ValueCountFrequency (%)
/6
75.0%
_2
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII87
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r10
 
11.5%
o9
 
10.3%
e8
 
9.2%
a7
 
8.0%
/6
 
6.9%
A5
 
5.7%
i5
 
5.7%
m4
 
4.6%
p3
 
3.4%
k3
 
3.4%
Other values (17)27
31.0%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing113
Missing (%)100.0%
Memory size1.0 KiB

Interactions

2022-09-05T21:51:14.338880image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:01.039673image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:02.082499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:03.100324image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:04.083826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:05.076995image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:06.035186image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:07.114669image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:08.115439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:09.217313image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:10.171430image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:11.320612image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:12.359309image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:13.353997image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:14.408807image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:01.215080image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:02.149924image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:03.166535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:04.154228image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:05.148604image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:06.103175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:07.186180image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:08.190026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:09.281747image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:10.239524image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:11.391348image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:12.435296image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:13.423063image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:14.482994image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:01.284821image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:02.226043image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:03.242372image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:04.231617image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:05.224192image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:06.183648image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:07.263827image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:08.274825image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:09.348577image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:10.317262image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:11.467790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:12.516063image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:13.495536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:14.548893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:01.352032image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:02.299952image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:03.316357image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:04.306330image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:05.290869image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:06.260058image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:07.332169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:08.356440image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:09.411946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:10.453118image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:11.539256image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:12.589376image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:13.567017image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:14.614174image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:01.423440image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:51:02.371611image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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Correlations

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Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:51:26.126219image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:51:26.370690image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:51:26.654533image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:51:15.711123image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:51:16.759980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:51:17.285283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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12001718https://www.tvmaze.com/episodes/2001718/zona-komforta-s01-special-zona-komforta-osuitelno-specialnyj-vypuskЗона Комфорта. Ошуительно Специальный Выпуск1NaNinsignificant_special2020-12-302020-12-30T00:00:00+00:0015.0<p>A unique release of The Shocking Howe. Actors and writers of the "Comfort Zone" series will tell you how the project was created. Of course, everything is in the style of the Shocking Howe.</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/322/807322.jpghttps://static.tvmaze.com/uploads/images/original_untouched/322/807322.jpghttps://api.tvmaze.com/episodes/200171851510https://www.tvmaze.com/shows/51510/zona-komfortaЗона комфортаScriptedRussian[Comedy]EndedNaN29.02020-10-222022-03-02https://okko.tv/serial/zona-komforta[Monday, Thursday]NaN34NaN366.0OkkoNaNNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/706515.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/706515.jpgNone1649573482https://api.tvmaze.com/shows/51510https://api.tvmaze.com/episodes/2287139Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21987721https://www.tvmaze.com/episodes/1987721/passaziry-1x03-kirillКирилл13.0regular2020-12-302020-12-30T00:00:00+00:0020.0NoneNaNhttps://static.tvmaze.com/uploads/images/medium_landscape/292/731145.jpghttps://static.tvmaze.com/uploads/images/original_untouched/292/731145.jpghttps://api.tvmaze.com/episodes/198772152499https://www.tvmaze.com/shows/52499/passaziryПассажирыScriptedRussian[Drama, Supernatural]EndedNaN23.02020-12-242022-05-27https://start.ru/watch/passazhiry[Friday]NaN82NaN245.0StartNaNNoneNaNNaN393530.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/394/986714.jpghttps://static.tvmaze.com/uploads/images/original_untouched/394/986714.jpgNone1661864044https://api.tvmaze.com/shows/52499https://api.tvmaze.com/episodes/2270905Russian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32386111https://www.tvmaze.com/episodes/2386111/xian-feng-jian-yu-lu-1x52-episode-52Episode 52152.0regular2020-12-3010:002020-12-30T02:00:00+00:008.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/238611149206https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-luXian Feng Jian Yu LuAnimationChinese[Action, Anime, Fantasy, Supernatural]Running8.07.02020-07-11Nonehttps://v.qq.com/detail/m/mzc00200hc38s5x.html10:00[Wednesday, Saturday]NaN62NaN104.0Tencent QQNaNhttps://v.qq.com/NaNNaN386423.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>1662275668https://api.tvmaze.com/shows/49206https://api.tvmaze.com/episodes/2386129ChinaCNAsia/ShanghaiNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1101958869https://www.tvmaze.com/episodes/1958869/wwe-nxt-14x53-main-event-johnny-gargano-c-vs-leon-ruff-for-the-nxt-north-american-championshipMain Event: Johnny Gargano (c) vs. Leon Ruff for the NXT North American Championship1453.0regular2020-12-3020:002020-12-31T01:00:00+00:00127.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/19588692266https://www.tvmaze.com/shows/2266/wwe-nxtWWE NXTSportsEnglish[]Running120.077.02010-02-23Nonehttp://www.wwe.com/inside/networkschedule20:00[Tuesday]7.292NaN15.0WWE NetworkNaNNoneNaN25100.0144541.0tt1601141https://static.tvmaze.com/uploads/images/medium_portrait/401/1002762.jpghttps://static.tvmaze.com/uploads/images/original_untouched/401/1002762.jpg<p>Each Wednesday at 8:00 p.m. ET, WWE Superstars and Divas of tomorrow face off on <b>WWE NXT</b><i>,</i> a one-hour weekly show that features the brightest and best of WWE's rising stars. WWE NXT showcases the Superstars and Divas from WWE's Performance Center as well as appearances from WWE Superstars and Legends in an intimate setting. WWE NXT broadcasts from the state-of-the-art Full Sail LIVE venue on the Full Sail University in campus in Orlando, Florida.</p>1661969159https://api.tvmaze.com/shows/2266https://api.tvmaze.com/episodes/2383154United StatesUSAmerica/New_YorkNaNhttps://api.tvmaze.com/episodes/2367107NaNNaNNaN30.0USA NetworkUnited StatesUSAmerica/New_YorkNaNNaNNaN
1112041985https://www.tvmaze.com/episodes/2041985/submission-underground-2020-12-30-submission-underground-20-bader-vs-fowlerSubmission Underground 20: Bader vs. Fowler202010.0regular2020-12-3020:002020-12-31T01:00:00+00:00120.0NoneNaNNaNNaNhttps://api.tvmaze.com/episodes/204198550162https://www.tvmaze.com/shows/50162/submission-undergroundSubmission UndergroundSportsEnglish[]Running120.0120.02016-07-17Nonehttps://www.tapology.com/fightcenter/promotions/2861-submission-underground-sug20:00[Saturday]NaN13NaN45.0UFC Fight PassNaNNoneNaNNaN387946.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/271/679188.jpghttps://static.tvmaze.com/uploads/images/original_untouched/271/679188.jpg<p>Submission Underground is a grappling event presented by Chael Sonnen and UFC Fight Pass!</p>1614930973https://api.tvmaze.com/shows/50162https://api.tvmaze.com/episodes/2041986United StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1121985214https://www.tvmaze.com/episodes/1985214/noblesse-1x13-noblesse-take-her-handNoblesse / Take Her Hand113.0regular2020-12-3000:002020-12-31T05:00:00+00:0025.0<p>Raizel appears in front of Raskreia and the Clan Leaders to prevent Gejutel's sentence from being carried out and put things in order. The Clan Leaders are overwhelmed by his incredible power. The real reason why the Previous Lord died is finally revealed. The battle between Lord and Noblesse begins!</p>NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/292/732081.jpghttps://static.tvmaze.com/uploads/images/original_untouched/292/732081.jpghttps://api.tvmaze.com/episodes/198521449732https://www.tvmaze.com/shows/49732/noblesseNoblesseAnimationJapanese[Anime, Supernatural]Ended25.025.02015-12-042020-12-30https://noblesse-anime.com/00:00[Wednesday]NaN44NaN20.0CrunchyrollNaNNoneNaNNaN386818.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/268/670751.jpghttps://static.tvmaze.com/uploads/images/original_untouched/268/670751.jpg<p>Raizel awakens from his 820-year slumber. He holds the special title of Noblesse, a pure-blooded Noble and protector of all other Nobles. In an attempt to protect Raizel, his servant Frankenstein enrolls him at Ye Ran High School, where Raizel learns the simple and quotidian routines of the human world through his classmates. However, the Union, a secret society plotting to take over the world, dispatches modified humans and gradually encroaches on Raizel's life, causing him to wield his mighty power to protect those around him... After 820 years of intrigue, the secrets behind his slumber are finally revealed, and Raizel's absolute protection as the Noblesse begins!</p>1648716882https://api.tvmaze.com/shows/49732https://api.tvmaze.com/episodes/1985214NaNNaNNaNNaNNaNNaNNaNNaN132.0Tokyo MXJapanJPAsia/TokyoNaNNaNNaN